- Email: [email protected]
Medical workstations for applied imaging and graphics research
Computerized Medical Imaging and Graphics, Vol. 18. No. 6, pp. 403-41 I. 1994 Copyright 0 1994 Ekvier Science Ltd Printed in the USA. All rights reserved 0895-61 I l/94 $6.00 + .OO
Pergamon 0895-6111(94)00024-7
MEDICAL
WORKSTATIONS AND GRAPHICS
Hans-Heino
FOR APPLIED RESEARCH
IMAGING
Ehricke*‘, Thomas Grunert+, Thomas Rupert Kolb$, and Martin Skalejs
Buck+,
*Department
of Electrical Engineering, Polytechnical University of Stralsund, Stralsund, Germany +I)epartment of Graphical-Interactive Systems, University of Tiibingen, Wilhelm-Schickhard Institute for Informatics, Tiibingen, Germany ‘University of Neuroradiology, University Hospitals of Tiibingen, Tiibingen, Germany (Received 22 February 1994)
Abstract-We present a medical workstation for the efficient implementation of research ideas related to image processing and computer graphics. Based on standard hardware platforms the software system encompasses two major components: A turnkey upplicution system provides a functionality kernel for a broad community of clinical users working with digital imaging devices, including methods of noise suppression, interactive and automatic segmentation, 3D surface reconstruction and multi-modal registration. A developnrenr toolbox allows new algorithms and applications to be efficiently implemented and consistently integrated with the common framework of the turnkey system. The platform is based on an elaborate object class structure describing objects for image processing, computer graphics, study handling and user interface control. Thus expertise of computer scientists familiar with this application domain is brought into the hospital and can be readily used by clinical researchers. Key Words: Computer
graphics,
Digital image processing,
Medical workstations,
INTROIXJCTION
development
velopment. For a research platform this is an intolerable feature. With respect to application development support a number of toolboxes with a focus on scientific visualization have been proposed ( 1,2). They enhance rapid prototyping by making available various image processing and graphics methods. These can be assembled to application pipelines by visual programming editors. Most of them allow for the integration of selfwritten software modules. However, the required pipeline structure of applications built in this manner poses severe restrictions on their complexity. Moreover, the programmer does not have much influence on the user interface of the program generated with these tools and thus the special requirements of clinical users as to man-machine interfaces cannot be met. Finally, they lack turnkey components providing base functionality (e.g., loading and interpreting image files, study handling, contrast and brightness adjustment, zooming, paning) which needs great efforts to be developed from scratch. The same argument is true for development libraries, such as the object-oriented one proposed in (3). This system focuses specifically on biomedical applications, but due to the high complexity of the objects library and the lack of elements for user interface development requires substantial algorithmic knowledge and elaborate programming skills. Therefore it is well suited for professional software developers, but not for clinical researchers. A few clinically oriented research
The impact of computer technology on medical research has undoubtedly grown during the last decade. In a variety of disciplines clinical researchers are increasingly confronted with the problem of making efficient use of digital equipment. The availability of powerful workstation hardware has enabled substantial advances in medical imaging and graphics. However, progress frequently is hampered by the lack of adequate software tools allowing research ideas to be rapidly realized. In the past clinical researchers have spent a tremendous amount of time to integrate new algorithms into modality consoles or develop application programs from scratch on standalone workstations. Commercially available application systems (e.g., MIP 3D, Kontron, Eching; Allegro. ISG Techn. Inc., Toronto; ANALYZE, CNSoftware, Southwater) are of limited use with respect to this problem. They offer a great number of graphics and image processing methods together with a clinically oriented user interface. However, they cannot easily be extended by new algorithms and applications since they support neither the consistent integration of new modules, nor their rapid de-
’Correspondence partment Stralsund,
Application
should be addressed to H.-H. Ehricke. Deof Electrical Engineering, Polytechnical University of GrofJe Parower StraOe 145, 18435 Stralsund, Germany.
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groups have proposed application systems with a focus on software ergonomics and functionality (4-7). Some of them try to achieve system extensibility by providing source code and/or a functions library for application development, but this is not the main subject of their work. CONCEPT
OF A MEDICAL WORKSTATION
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Usmlntnfcia iktem Sian
RESEARCH
Although our concept of a medical graphics workstation focuses on development support for novel algorithms and applications, we have integrated a readyto-use application system (see Fig. 1). This provides user interface, base functionality (e.g., study handling, multiplanar reconstruction, 3D surface visualization, geometric image analysis) and applications (e.g., semiautomatic segmentation, multimodality matching, morphometry), which are typically found as part of routine systems (e.g., modality consoles) and serves as a common framework for application development. We are aware of the fact that especially for legal reasons a clear distinction between routine and research equipment is desirable. However, the following observations justify our concept of a research system with integrated routine features: 1. Many solution ideas expressed by clinicians focus on extensions of available routine methods; of routine functionality into a re2. The integration search platform makes it easier to become familiar with it and link research and routine work; 3. Integrating novel applications under a common user interface increases consistency and avoids getting lost in a variety of different interfaces; and 4. The cooperation between different functions and applications within a common environment increases software reusability. The basis for the application system as well as the development toolbox of the proposed platform is an elaborate object class structure. Perhaps one of the most promising characteristics of the object-orientation paradigm which has revolutionized software technology is its know-how transfer capability. Let us briefly explain this statement: The design of an adequate object class structure requires a great deal of knowledge and experience in the problem domain. Thus, an object class library does not merely provide functionality as, for example, a functions library. By the configuration of object classes, their methods and attributes and the class hierarchy, a great deal of expertise with respect to the problem domain is represented. This can be directly used by an application developer. Unlike a functions library an object class structure provides an ef-
Fig. I. Architectural system overview: The turnkey application system and the development toolbox are based on a common object class library.
ficient mechanism for the modeling of realworld objects by a software system. Thus, a problem-adequate software structure can be designed, even by a non-expert in the application domain. We propose an object class library falling into two categories: 1. Objects interfacing the turnkey application system (management objects); and 2. Turnkey system independent objects for algorithmic research and application development (image processing and graphics objects). The latter allow for an easy and quick application development by providing structure and functionality of most real-world objects in the area of medical imaging and graphics. Examples are a 3D-renderer for the threedimensional visualization of volumetric datasets, a digital filter for the enhancement of images e.g. by noise suppression and a registrator for matching multi-modal datasets. A consistent integration of new applications into the turnkey system may be performed by use of the interfacing objects. These provide methods for user interface access as well as study handling. CLINICAL
REQUIREMENTS FUNCTIONALITY
AND
BASIC
As already discussed in the previous chapter we regard the turnkey part of our platform as a means of providing base functionality and a common framework for the consistent integration of novel algorithms and applications. One of the primary goals of the system is to address a broad community of clinical clients who use digital images as an information medium. Partic-
Workstations for imaging and graphics research
ularly by the advent of new imaging modalities, such as Digital Subtraction Angiography (DSA), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), the penetration of radiology departments with digital images has considerably increased. Besides radiology, a variety of clinical disciplines are more and more equipped with digital1 imaging devices. Examples are: Ophthalmology (laser-scan images of the retina); Nuclear medicine (scintigraphs, Positron Emission Tomography); Cardiology (digitized ultrasound data); Anatomy (scanned photographs, digital anatomic atlas); and Pathology (digital microscopy) The list may be extended for example by those departments in a hospital which are traditional radiology customers, but have an interest in postprocessing the acquired image data for therapy planning purposes (e.g., neurosurgery and orthopedics). Therefore a requirements analysis for a medical workstation has to cover various disciplines. We performed such an analysis at the University Hospitals of Tubingen. Our results document an astonishingly large overlap of the requirements of the investigated disciplines. From this we have derived a functionality specification of a universal medical imaging and graphics workstation. The focus here is not on exotic applications which are of interest only for a small group of specialists, but on a universal functionaliiy kernel. We distinguish between five functionality categories: 1. Access: Image storage/retrieval, data compression, file format interpretation (esp. ACR-NEMA, DICOM), study handling., multiple images display. operations (e.g. 2. Manipulation: Image processing zoom, pan, mirror, contrast/brightness adjustment, negate, filter, image arithmetics). greyvalue statistics, geo3. Evaluation: Local/global metric properties (2D/3D distance, angle, profile), time-series analysis. hardcopy, re4. Documentation: Image annotation, porting. 5. Analysis: Advanced image processing and graphics (e.g., segmentation, multi-modal registration, tissue classification, multiplanar reconstruction, volume rendering). THE LIGHTBOX METAPHER FOR USER INTERFACE DESIGN Especially in medical informatics the success of a digital system largely depends on the adequacy of its man-machine interface. A possible strategy in user in-
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terface (UI) design is the analysis of the way physicians deal with real-world objects which will have a representation within the software system under development. In the context of medical imaging and graphics real-world objects familiar to physicians are the lightbox and X-ray films. They are by far the most common media for viewing medical images, even if those were acquired by digital devices. Why is the lightbox the most successful viewing station in medicine? Besides many other reasons we may identify some facts related to user interface design: 1. Viewing of radiographs is easily performed by taking them out of a folder and placing them arbitrarily to the lightbox; 2. A lightbox can hold various images of a patient and thus provide an excellent overview of one or several studies; 3. Switching between overview and detailed view is possible within a timeframe of milliseconds, just by head and eye motion; and of radiographs on a lightbox can 4. The configuration quickly be reorganized. We used these lightbox characteristics as a guideline to user interface design of our system. An overview of the proposed UI presentation layer is given by Fig. 2. The workstation screen is used almost entirely for image display. Only a small part is reserved as a menu field. Actions are triggered via mouse clicks. In analogy to the characteristics observed with the conventional counterpart of our system, the following look and feel is proposed: An image or a patient study can easily be selected from an iconized study folder and attached to an arbitrary lightbox segment via a drag and drop mechanism; The digital lightbox can simultaneously display up to 16 images from one or several patient studies; Unrestricted maneuvering on the lightbox panel which actually may be much bigger than the screen is performed by realtime zoom and pan. Thus the panel section actually displayed on the screen and its spatial resolution is controlled; and The logical link between images and lightbox segments can be graphically reorganized on a lightbox overview icon. Although we have based the design of our user interface on the lightbox metapher we have not restricted ourselves to a mere ZD-medium. Many additional features, such as fast skiming through an image series, arbitrary slicing through a volume dataset or projection onto a plane, enhance the interpretation process.
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Fig. 2. User interface
presentation
layer of the application
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system: The workstation
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screen is used almost entirely
for image display; only a small part is reserved as a menu field.
EXTENSION INTERFACE AND DEVELOPMENT TOOLBOX A medical imaging and graphics workstation suitable for clinical research must contain mechanisms for application development support and integration of new algorithms. Our concept of an extensible platform is based on the following observation: A mere toolsystern without a common integration framework will lead to the development of many standalone applications. This seems not very efficient because base functionality elements necessary for any application, like loading patient data, interpretation of file formats or display management are not reused. Moreover, the creation of different user interfaces will result in a great deal of learning efforts for the medical staff in order to get familiar with a new application. A third problem is the great overhead necessary for data import and export if two applications are to be combined in a certain case. For these reasons we propose a common integration framework which is given by the already described turnkey application system and an elaborate extension interface. Figure 3 illustrates the mechanism of integrating a new application into the turnkey system. Usually a new application is integrated into the workstation interface as an iconized application button
within the menu field. By pressing this button the user invokes the application and as an example, an application specific popup-menu is displayed. From the programmer’s view two object classes play an important role here: (a) User interface control classes; and (b) Patient study handling classes. Let us briefly explain their meaning: User interface control objects manage the behavior and look of the common user interface. They contain methods e.g. for enabling/disabling menu buttons, mouse drawing of a polygon within an image and display of an image at a certain screen location. A patient study may contain textual elements (e.g., patient name, medical report, anamnesis), graphical objects, images and audio. Study handling classes provide methods for accessing and manipulating these elements and their hierarchical structure. For example image data may be accessed by an application using a get-image or get-pixel-value method. New images may be displayed by transfering the data from the application object to a socalled result study which has been attached to an image display segment on the workstation screen. In this way display management and study handling are performed by the turnkey system and the application programmer does not have to bother for this highly complex task.
Workstations for imaging and graphics research
Turnkgr
r-
Fig. 3. Principle
??
H.-H. EHRICKEet al
Worketation
User Interfkace
of integrating
a new application
into the turnkey
workstation
via the user interface control and
patient study handling objects.
Besides the integration interface the application builder toolbox is another key element of our development system. Its basis is an object class library which covers a broad spectrum of medical imaging and graphics functionality. Its structure represents a great deal of software development expertise in this area and therefore allows inexperienced application programmers to quickly arrive at a professional program design. The class library contains a variety of C++ classes developed at our institute and integrates a commercial system (Imaging Applicalions Platform, ISG Techn. Inc., Toronto) which we found to be of good adequacy for this purpose. The library encompasses objects and methods for image file format handling, image memory management, digital filtering, pixel value statistics, raycasting, dataset registration, geometric modeling, segmentation, surface reconstruction and many more. A detailed description of the object class structure is beyond the scope of this paper. Our design was guided by the endeavour to support application development as well as algorithmic research. Especially the latter led to a sophisticated structure with many levels in the inheritance hierarchy for a number of classes, thus providing high flexibility. CLINICAL
ISVALUATION
In collaboration with the University Hospitals of Tiibingen, Eye Clinic, Radiological Clinic and Surgical
Clinic, an evaluation of both components of the platform was performed. The prototypical development of the turnkey system allowed for an early presentation to clinicians. On the other hand, the toolbox system, on which we focus here, required a higher state of completeness in order to be evaluated. As a prerequisite a stable object class structure for user interface control, patient study handling, computer graphics and image processing had to be available. Our evaluation of the toolkit focused on the question: What impact does the tool have on the output of clinical research? The system has been used for the implementation of various research projects, including 1. Diagnosis of degenerative brain disorders by Magnetic Resonance based volumetry; of vascular detail by interactive 3D 2. Analysis walkthrough simulations of Magnetic Resonance Angiography datasets; 3. Integrated 3D visualization of vascular structures and soft-tissue for neurosurgery planning (see Fig. 4); 4. Cerebral angioma radiosurgery planning; of endorectal 5. Surgery planning by 3D visualization ultrasound data; (see 6. Use of a digital brain atlas in neuroradiology Fig. 5); 7. Analysis of time-series of retinal laserscan images in ophthalmology; planning of auditory aids: 8. CT-based implantation and
Computerized
Medical Imaging and Graphics
Fig. 4. Integrated 3D visualization of brain anatomy and adjacent vasculature for neurosurgery planning. Brain surface (upper left) and vasculature (upper right) were integrated with a multi-modal 3D renderer (lower left and right).
9. Generation model.
of a three-dimensional
anatomic
heart
We layed particular emphasis on three criteria: (a) Efficiency, (b) Flexibility, and (c) Usability. Eficiency relates to the question: How long does it take to implement a research application by use of the toolkit? We found that especially researchers with little programming skills had difficulties in becoming familiar with the toolkit. This is due to the fact that with the current implementation of our toolbox as a prerequisite basic knowledge of Unix, C, C++ and X 1 l/Motif is required. Particularly by the availability of well documented example programs the learning phase could be considerably shortened. Involved physicians had a lot of experience with the implementation of research ideas e.g. on modality consoles or workstations by use of a simple functions library written in FORTRAN. This served as the basis for efficiency evaluation. Due to the learning phase the development time was prolonged in the beginning. However, within a timeframe of three months it gradually decreased to between one half and one third of the time necessary for the traditional approach. Especially applications based on complex algorithms benefited from the available object classes because those hide implementation details from the programmer. With respect toflexibility we investigated whether all the research projects mentioned above could be comfortably implemented with the tool. Since our system is open and freely program-
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mable only few restrictions exist. These result from user interface consistency considerations. Due to the limitations of their traditional programming approach the clinical researchers had developed remarkable skills in finding workarounds. Therefore they did not feel restricted by the system architecture in any way. Usability refers to the adequacy of the workstation to be readily used within the clinical environment. Since clinical researchers usually cannot make an absolute clear distinction between routine work and research, an architecture providing routine functionality together with an extension toolbox found good acceptance. However, within the turnkey application system they missed some functions available on dedicated modality consoles. Although our system intends to support any modality it is difficult to provide the whole spectrum of modality specific functions on a single platform. Network integration and file transfer interfaces are other crucial factors which determine the usability of the system. In our current implementation images are transferred from the modalities to the workstation database via ethernet and FTP (file transfer protocol). This is not a comfortable but practical solution and for research applications seems to be sufficient. However, for routine clinical use a direct link to the modality patient and image databases is a prerequisite. This confronts us with a severe problem because manufacturers of imaging equipment seldom have a PACS (Picture Archiving and Communication System) interface or are reluctant to open it to third parties. Of particular value is the availability of an image10 object which allows for the interpretation of various image file formats. CLINICAL EXAMPLE: AN ADJUSTABLE DIGITAL BRAIN ATLAS IN NEURORADIOLOGY As mentioned in the previous chapter the platform has been used for the implementation of various clinical applications. As an example we will elaborate here on the digital brain atlas application. Here we use the Karolinska digital brain atlas (8) which we have integrated as part of the medical workstation database for the interpretation of positron emission tomography (PET) images, for multi-modality matching or for quantitative analysis of MRI or CT datasets as a knowledge base for automatic segmentation. From the computer science point of view the main problem consists of the matching of atlas structures to the individual patient anatomy and the visualization of the results. The realized approach encompasses mainly two steps. First, a rigid registration of the atlas with the 3D patient dataset is achieved by manual interaction. Changes of
Workstations for imaging and graphics research
transformation parameter,5 (translation, rotation, scaling) are immediately visualized on the workstation screen by a three-dimensional scene showing, for example, three orthogonal cuts through the patient volume with an integrated surface representation of the selected atlas structure (see Fig. 5). Second, an elastic matching procedure can be applied in order to exactly adjust the atlas by local deformations. Let us briefly explain how the medical workstation was used to realize this nevv application: We focus here on step one of the approach. Figure 6 illustrates the implementation mechanism. It gives a rough overview of the objects which have been used, their location within the overall system and the underlying dataflow concept. For reasons of caNmprehensiveness we ignore user interface related objects here. The turnkey application system allows patient images and atlas structures to be loaded from the database into the workstation’s main memory and to be displayed on the screen. The mesh and volumeset objects provide adequate datastructures together with methods to manipulate and access the data. The application is activated by mouse clicking the corresponding icon button within the menu field. It accesses patient as well as atlas data via the study handling interface. Get-voxel-set and get-mesh methods yield pointers to the voxelset and mesh ob-
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EHRICKE et al.
409
jects. Within the mesh object an atlas structure is represented as a triangulated surface description. This is transformed into a binary volume dataset by a voxelizer object. After each interactive modification of the transformation parameters which describe the spatial relation of the two datavolumes in a three-dimensional world coordinate system, a multi-modal 3D renderer is activated. This generates a 3D projection image (similar to Fig. 5) by simultaneously raycasting the two datavolumes and merging corresponding rays. The resulting image is stored within a picture object and given back to the turnkey system via the study handling interface. Here it is displayed and can be saved into the patient database or hardcopied. The implementation source code is short, because the voxelizer, voxelset, raycaster and picture objects already exist within the toolbox’s object class library. The application developer’s task was (a) to create a raymerger object; (b) to program the logical link between the objects used; and (c)to connect the user interface with the methods provided by the objects. Our evaluation results suggest that clinical research related to digital imaging and graphics benefits from the availability of the proposed toolkit system in three ways: First, the path from a research idea to its imple-
Fig. 5. 3D scene illustrating mesencephalon surface (dark) from a digital brain atlas matched to a magnetic resonance
patient dataset.
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Medical Imaging and Graphics
Fig. 6. Object structure of the atlas-guided neuroradiological diagnosis application. A great amount of functionality is already provided by the turnkey application system.
mentation and evaluation is shortened. Second, the clinical availability of a variety of image processing and graphics methods motivates novel applications and the quick realization of new methods becomes possible. Third, the communication between clinical researchers and computer scientists is supported since the platform can be used as a medium for the presentation of ideas. However, the programming knowledge necessary to efficiently use our toolbox, has been an obstacle for addressing a broader community of clinical researchers. As a solution we propose a graphical programming interface which we know from commercial user interface builders or visual programming tools, such as AVS (Stardent Inc., Concord) and Explorer (Silicon Graphics, Mountain View). Its kernel will be a graphical object assembly editor allowing both, user interface objects and image analysis and synthesis objects to be selected and grouped together as an application specific object network on the workstation screen via mouse input. SUMMARY Today, the efficient use of computer platforms is of high relevance for the output of medical research in
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most clinical disciplines. The necessary knowledge and occupancy with computer science facts absorbs the attention of researchers from clinical issues. We tackle this problem by proposing an easy-to-use medical workstation system. This can be used as a tool for the efficient development of innovative applications in all clinical disciplines where digital images are acquired or used. The turnkey component of the system provides a great deal of ready-to-use functionality which is typically found as part of modality consoles. A graphical user interface simulating the look and feel of a conventional lightbox allows for an easy access to these methods. An integrated development toolbox enables researchers quickly to realize new ideas by assembly of already available software modules implemented as an object class library. The latter encompasses a variety of image processing and computer graphics methods grouped together with efficient data structures. It furthermore provides mechanisms to interface the turnkey workstation allowing new applications to be easily and consistently integrated and thus be linked to existing functionality. This is demonstrated by an application example: The graphically-interactive registration of a digital brain atlas with tomographic patient volumes. Our evaluation results suggest the extension of the toolbox by a visual programming editor for researchers who do not possess any programming skills. The described strategy avoids the problem of software heterogeneity and shortens the path of a new application into the clinical routine environment.
Acknowkedgmenfs-The
authors are grateful to Lennart Thrutjell,
Uppsala University, for his kind assistance of the digital brain atlas database.
with the implementation
REFERENCES 1. Upson, C.; Faulhaber, T.; Kamins, D.; Laidlaw, D.; Schlegel, D.; Vroom, J.; Gurwitz, R.; van Dam, A. The application visualization system: A computational environment for scientific visualization. IEEE Comput. Graph. Applications 9(4):30-42; 1989. 2. Dyer, D. S. A dataflow toolkit for visualization. IEEE Comput. Graph. and Applications 10:60-69, 1990. 3. Heffeman, P.; and Dekel, D. Imaging applications platform: Concept to implementation. In: Robb, R. A. ed. Bellingham: SPIE; Visualization Biomed. Comput. 1992:495-509. 4. Ho, B. K. T.; Ratib, 0.; and Hot-ii, S. C. PACS workstation design. Comput. Med. Imag. Graph. 15(3):147-155, 1991. 5. Staemmler, M.; Brill, R.; Becker, K.; Folkerts, K.-H.; and Gersonde, K. SUNRISE a software system for medical imaging analysis. In H. U. Lemke, M. L. Rhodes, C. C. Jaffe, and R. Felix, editors, Comput. Assist. Radiol., pages 671-677, Berlin, Heidelberg, New York, 1989. Springer. 6. Dahm, M.; Glaser, K.; Jansen-Dittmer, H.; Keizers, A.; Krueger, P.; Meyer-Ebrecht, D.; Miinker-Kaupp, K.; Rudolf, H.; Schilhng, C.; Sieslack, R.; Winkler, W.; Wein, B.; and Gunther, R. Ra-
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for imaging and graphics
diologists start designing their digital workplace: prototyping with a digital image workstation in the radiology. In H. U. Lemke, M. L. Rhodes, C. C. Jafte, and R. Felix, editors, Comput. Assist. Radiol. pages 699-704, Berlin, Heidelberg, New York, 1991. Springer. 7. Ehricke, H.-H.; and &had, L. R. MRA-guided radiation treatment planning for cerebral angiomas. Comput. Med. Imag. Graph. 16(Z); 1992. 8. Greitz, T.; Holte, S.; Bohm, C.; Eriksson, L.; Seitz, R.; Ericson, K.; Nyblck, H.; and Stone-Elander, S. A database library as a diagnostic aid in neuroimaging. Neuroradiology 33(Suppl.):24, 1991.
EHRICKEreceived the MS. degree in medical informatics from the University of Heidelberg in 1988. In the same year he joined the Siemens Medical Engineering Group, Erlangen, as a research specialisl. in medical imaging. In 1991 he received his Ph.D. in computer science from the University of Heidelberg in collaboration with the German Cancer Research Center. In 1992 he joined the University of Tiibingen, Wilhelm-Schickard Institute for Informatics as an assistant professor for computer graphics and image processing. Since 1994 he holds the position of a professor at the Polytechnical University of Stralsund, Department of Electrical Engineering. His primary interest is in medical imaging, computer graphics and object-orimznted software engineering.
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degree in 1992. He is currently working on his Ph.D. in computer science at the WSI/GRIS computer graphics lab, University of Tiibingen, where he is focusing on research in the areas ofimage processing and application development systems for computer graphics in medicine. About the Author-THOMAS BUCK studied mechanical engineering at the Escola Polit&nica, Universidade Federal da Bahia, Brasil, where he received his B.Sc. in 1986. He received the M.Sc. in electrical engineering from the Faculdade de Engenharia El&ica, Universidade Estadual de Campinas, Brasil, in 1989. He is currently completing his Ph.D. in computer science at the WSI/GRIS computer graphics lab, University of Tiibingen, Germany. His research interests are digital image processing, computer graphics and artificial intelligence, and their application to medical sciences.
About the Author-HANS-HEINO
About the Author-THOMAS GRUNERT studied physics at the University of Tiibingen, Germany, where he received the BSc. and MSc.
About the Author-RUPERT KOLB studied Physics at the University of Tiibingen, Germany, where he received his M.Sc. in 199 I. He is currently a research assistant at the Department of Neuroradiology, University Hospitals of Tiibingen, working on a Ph.D. in computer science. His research interests include digital image processing, fast volume rendering and their applications to the neurosciences.
About the Author-MARTIN SKALEJ studied medicine at the University of Mainz, Germany, where he received his M.D. in 1986. Funded by the Deutsche Forschungsgemeinschaft he joined the University of Tiibingen in 1986 where he currently is a member of the Department of Neuroradiology. His major interests are magnetic resonance imaging, digital image processing, computer graphics and their application to the neurosciences.
Pergamon 0895-6111(94)00024-7
MEDICAL
WORKSTATIONS AND GRAPHICS
Hans-Heino
FOR APPLIED RESEARCH
IMAGING
Ehricke*‘, Thomas Grunert+, Thomas Rupert Kolb$, and Martin Skalejs
Buck+,
*Department
of Electrical Engineering, Polytechnical University of Stralsund, Stralsund, Germany +I)epartment of Graphical-Interactive Systems, University of Tiibingen, Wilhelm-Schickhard Institute for Informatics, Tiibingen, Germany ‘University of Neuroradiology, University Hospitals of Tiibingen, Tiibingen, Germany (Received 22 February 1994)
Abstract-We present a medical workstation for the efficient implementation of research ideas related to image processing and computer graphics. Based on standard hardware platforms the software system encompasses two major components: A turnkey upplicution system provides a functionality kernel for a broad community of clinical users working with digital imaging devices, including methods of noise suppression, interactive and automatic segmentation, 3D surface reconstruction and multi-modal registration. A developnrenr toolbox allows new algorithms and applications to be efficiently implemented and consistently integrated with the common framework of the turnkey system. The platform is based on an elaborate object class structure describing objects for image processing, computer graphics, study handling and user interface control. Thus expertise of computer scientists familiar with this application domain is brought into the hospital and can be readily used by clinical researchers. Key Words: Computer
graphics,
Digital image processing,
Medical workstations,
INTROIXJCTION
development
velopment. For a research platform this is an intolerable feature. With respect to application development support a number of toolboxes with a focus on scientific visualization have been proposed ( 1,2). They enhance rapid prototyping by making available various image processing and graphics methods. These can be assembled to application pipelines by visual programming editors. Most of them allow for the integration of selfwritten software modules. However, the required pipeline structure of applications built in this manner poses severe restrictions on their complexity. Moreover, the programmer does not have much influence on the user interface of the program generated with these tools and thus the special requirements of clinical users as to man-machine interfaces cannot be met. Finally, they lack turnkey components providing base functionality (e.g., loading and interpreting image files, study handling, contrast and brightness adjustment, zooming, paning) which needs great efforts to be developed from scratch. The same argument is true for development libraries, such as the object-oriented one proposed in (3). This system focuses specifically on biomedical applications, but due to the high complexity of the objects library and the lack of elements for user interface development requires substantial algorithmic knowledge and elaborate programming skills. Therefore it is well suited for professional software developers, but not for clinical researchers. A few clinically oriented research
The impact of computer technology on medical research has undoubtedly grown during the last decade. In a variety of disciplines clinical researchers are increasingly confronted with the problem of making efficient use of digital equipment. The availability of powerful workstation hardware has enabled substantial advances in medical imaging and graphics. However, progress frequently is hampered by the lack of adequate software tools allowing research ideas to be rapidly realized. In the past clinical researchers have spent a tremendous amount of time to integrate new algorithms into modality consoles or develop application programs from scratch on standalone workstations. Commercially available application systems (e.g., MIP 3D, Kontron, Eching; Allegro. ISG Techn. Inc., Toronto; ANALYZE, CNSoftware, Southwater) are of limited use with respect to this problem. They offer a great number of graphics and image processing methods together with a clinically oriented user interface. However, they cannot easily be extended by new algorithms and applications since they support neither the consistent integration of new modules, nor their rapid de-
’Correspondence partment Stralsund,
Application
should be addressed to H.-H. Ehricke. Deof Electrical Engineering, Polytechnical University of GrofJe Parower StraOe 145, 18435 Stralsund, Germany.
403
Computerized
404
Medical Imaging and Graphics
groups have proposed application systems with a focus on software ergonomics and functionality (4-7). Some of them try to achieve system extensibility by providing source code and/or a functions library for application development, but this is not the main subject of their work. CONCEPT
OF A MEDICAL WORKSTATION
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1994. Volume
18, Number
6
Usmlntnfcia iktem Sian
RESEARCH
Although our concept of a medical graphics workstation focuses on development support for novel algorithms and applications, we have integrated a readyto-use application system (see Fig. 1). This provides user interface, base functionality (e.g., study handling, multiplanar reconstruction, 3D surface visualization, geometric image analysis) and applications (e.g., semiautomatic segmentation, multimodality matching, morphometry), which are typically found as part of routine systems (e.g., modality consoles) and serves as a common framework for application development. We are aware of the fact that especially for legal reasons a clear distinction between routine and research equipment is desirable. However, the following observations justify our concept of a research system with integrated routine features: 1. Many solution ideas expressed by clinicians focus on extensions of available routine methods; of routine functionality into a re2. The integration search platform makes it easier to become familiar with it and link research and routine work; 3. Integrating novel applications under a common user interface increases consistency and avoids getting lost in a variety of different interfaces; and 4. The cooperation between different functions and applications within a common environment increases software reusability. The basis for the application system as well as the development toolbox of the proposed platform is an elaborate object class structure. Perhaps one of the most promising characteristics of the object-orientation paradigm which has revolutionized software technology is its know-how transfer capability. Let us briefly explain this statement: The design of an adequate object class structure requires a great deal of knowledge and experience in the problem domain. Thus, an object class library does not merely provide functionality as, for example, a functions library. By the configuration of object classes, their methods and attributes and the class hierarchy, a great deal of expertise with respect to the problem domain is represented. This can be directly used by an application developer. Unlike a functions library an object class structure provides an ef-
Fig. I. Architectural system overview: The turnkey application system and the development toolbox are based on a common object class library.
ficient mechanism for the modeling of realworld objects by a software system. Thus, a problem-adequate software structure can be designed, even by a non-expert in the application domain. We propose an object class library falling into two categories: 1. Objects interfacing the turnkey application system (management objects); and 2. Turnkey system independent objects for algorithmic research and application development (image processing and graphics objects). The latter allow for an easy and quick application development by providing structure and functionality of most real-world objects in the area of medical imaging and graphics. Examples are a 3D-renderer for the threedimensional visualization of volumetric datasets, a digital filter for the enhancement of images e.g. by noise suppression and a registrator for matching multi-modal datasets. A consistent integration of new applications into the turnkey system may be performed by use of the interfacing objects. These provide methods for user interface access as well as study handling. CLINICAL
REQUIREMENTS FUNCTIONALITY
AND
BASIC
As already discussed in the previous chapter we regard the turnkey part of our platform as a means of providing base functionality and a common framework for the consistent integration of novel algorithms and applications. One of the primary goals of the system is to address a broad community of clinical clients who use digital images as an information medium. Partic-
Workstations for imaging and graphics research
ularly by the advent of new imaging modalities, such as Digital Subtraction Angiography (DSA), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), the penetration of radiology departments with digital images has considerably increased. Besides radiology, a variety of clinical disciplines are more and more equipped with digital1 imaging devices. Examples are: Ophthalmology (laser-scan images of the retina); Nuclear medicine (scintigraphs, Positron Emission Tomography); Cardiology (digitized ultrasound data); Anatomy (scanned photographs, digital anatomic atlas); and Pathology (digital microscopy) The list may be extended for example by those departments in a hospital which are traditional radiology customers, but have an interest in postprocessing the acquired image data for therapy planning purposes (e.g., neurosurgery and orthopedics). Therefore a requirements analysis for a medical workstation has to cover various disciplines. We performed such an analysis at the University Hospitals of Tubingen. Our results document an astonishingly large overlap of the requirements of the investigated disciplines. From this we have derived a functionality specification of a universal medical imaging and graphics workstation. The focus here is not on exotic applications which are of interest only for a small group of specialists, but on a universal functionaliiy kernel. We distinguish between five functionality categories: 1. Access: Image storage/retrieval, data compression, file format interpretation (esp. ACR-NEMA, DICOM), study handling., multiple images display. operations (e.g. 2. Manipulation: Image processing zoom, pan, mirror, contrast/brightness adjustment, negate, filter, image arithmetics). greyvalue statistics, geo3. Evaluation: Local/global metric properties (2D/3D distance, angle, profile), time-series analysis. hardcopy, re4. Documentation: Image annotation, porting. 5. Analysis: Advanced image processing and graphics (e.g., segmentation, multi-modal registration, tissue classification, multiplanar reconstruction, volume rendering). THE LIGHTBOX METAPHER FOR USER INTERFACE DESIGN Especially in medical informatics the success of a digital system largely depends on the adequacy of its man-machine interface. A possible strategy in user in-
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terface (UI) design is the analysis of the way physicians deal with real-world objects which will have a representation within the software system under development. In the context of medical imaging and graphics real-world objects familiar to physicians are the lightbox and X-ray films. They are by far the most common media for viewing medical images, even if those were acquired by digital devices. Why is the lightbox the most successful viewing station in medicine? Besides many other reasons we may identify some facts related to user interface design: 1. Viewing of radiographs is easily performed by taking them out of a folder and placing them arbitrarily to the lightbox; 2. A lightbox can hold various images of a patient and thus provide an excellent overview of one or several studies; 3. Switching between overview and detailed view is possible within a timeframe of milliseconds, just by head and eye motion; and of radiographs on a lightbox can 4. The configuration quickly be reorganized. We used these lightbox characteristics as a guideline to user interface design of our system. An overview of the proposed UI presentation layer is given by Fig. 2. The workstation screen is used almost entirely for image display. Only a small part is reserved as a menu field. Actions are triggered via mouse clicks. In analogy to the characteristics observed with the conventional counterpart of our system, the following look and feel is proposed: An image or a patient study can easily be selected from an iconized study folder and attached to an arbitrary lightbox segment via a drag and drop mechanism; The digital lightbox can simultaneously display up to 16 images from one or several patient studies; Unrestricted maneuvering on the lightbox panel which actually may be much bigger than the screen is performed by realtime zoom and pan. Thus the panel section actually displayed on the screen and its spatial resolution is controlled; and The logical link between images and lightbox segments can be graphically reorganized on a lightbox overview icon. Although we have based the design of our user interface on the lightbox metapher we have not restricted ourselves to a mere ZD-medium. Many additional features, such as fast skiming through an image series, arbitrary slicing through a volume dataset or projection onto a plane, enhance the interpretation process.
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Fig. 2. User interface
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screen is used almost entirely
for image display; only a small part is reserved as a menu field.
EXTENSION INTERFACE AND DEVELOPMENT TOOLBOX A medical imaging and graphics workstation suitable for clinical research must contain mechanisms for application development support and integration of new algorithms. Our concept of an extensible platform is based on the following observation: A mere toolsystern without a common integration framework will lead to the development of many standalone applications. This seems not very efficient because base functionality elements necessary for any application, like loading patient data, interpretation of file formats or display management are not reused. Moreover, the creation of different user interfaces will result in a great deal of learning efforts for the medical staff in order to get familiar with a new application. A third problem is the great overhead necessary for data import and export if two applications are to be combined in a certain case. For these reasons we propose a common integration framework which is given by the already described turnkey application system and an elaborate extension interface. Figure 3 illustrates the mechanism of integrating a new application into the turnkey system. Usually a new application is integrated into the workstation interface as an iconized application button
within the menu field. By pressing this button the user invokes the application and as an example, an application specific popup-menu is displayed. From the programmer’s view two object classes play an important role here: (a) User interface control classes; and (b) Patient study handling classes. Let us briefly explain their meaning: User interface control objects manage the behavior and look of the common user interface. They contain methods e.g. for enabling/disabling menu buttons, mouse drawing of a polygon within an image and display of an image at a certain screen location. A patient study may contain textual elements (e.g., patient name, medical report, anamnesis), graphical objects, images and audio. Study handling classes provide methods for accessing and manipulating these elements and their hierarchical structure. For example image data may be accessed by an application using a get-image or get-pixel-value method. New images may be displayed by transfering the data from the application object to a socalled result study which has been attached to an image display segment on the workstation screen. In this way display management and study handling are performed by the turnkey system and the application programmer does not have to bother for this highly complex task.
Workstations for imaging and graphics research
Turnkgr
r-
Fig. 3. Principle
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Worketation
User Interfkace
of integrating
a new application
into the turnkey
workstation
via the user interface control and
patient study handling objects.
Besides the integration interface the application builder toolbox is another key element of our development system. Its basis is an object class library which covers a broad spectrum of medical imaging and graphics functionality. Its structure represents a great deal of software development expertise in this area and therefore allows inexperienced application programmers to quickly arrive at a professional program design. The class library contains a variety of C++ classes developed at our institute and integrates a commercial system (Imaging Applicalions Platform, ISG Techn. Inc., Toronto) which we found to be of good adequacy for this purpose. The library encompasses objects and methods for image file format handling, image memory management, digital filtering, pixel value statistics, raycasting, dataset registration, geometric modeling, segmentation, surface reconstruction and many more. A detailed description of the object class structure is beyond the scope of this paper. Our design was guided by the endeavour to support application development as well as algorithmic research. Especially the latter led to a sophisticated structure with many levels in the inheritance hierarchy for a number of classes, thus providing high flexibility. CLINICAL
ISVALUATION
In collaboration with the University Hospitals of Tiibingen, Eye Clinic, Radiological Clinic and Surgical
Clinic, an evaluation of both components of the platform was performed. The prototypical development of the turnkey system allowed for an early presentation to clinicians. On the other hand, the toolbox system, on which we focus here, required a higher state of completeness in order to be evaluated. As a prerequisite a stable object class structure for user interface control, patient study handling, computer graphics and image processing had to be available. Our evaluation of the toolkit focused on the question: What impact does the tool have on the output of clinical research? The system has been used for the implementation of various research projects, including 1. Diagnosis of degenerative brain disorders by Magnetic Resonance based volumetry; of vascular detail by interactive 3D 2. Analysis walkthrough simulations of Magnetic Resonance Angiography datasets; 3. Integrated 3D visualization of vascular structures and soft-tissue for neurosurgery planning (see Fig. 4); 4. Cerebral angioma radiosurgery planning; of endorectal 5. Surgery planning by 3D visualization ultrasound data; (see 6. Use of a digital brain atlas in neuroradiology Fig. 5); 7. Analysis of time-series of retinal laserscan images in ophthalmology; planning of auditory aids: 8. CT-based implantation and
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Fig. 4. Integrated 3D visualization of brain anatomy and adjacent vasculature for neurosurgery planning. Brain surface (upper left) and vasculature (upper right) were integrated with a multi-modal 3D renderer (lower left and right).
9. Generation model.
of a three-dimensional
anatomic
heart
We layed particular emphasis on three criteria: (a) Efficiency, (b) Flexibility, and (c) Usability. Eficiency relates to the question: How long does it take to implement a research application by use of the toolkit? We found that especially researchers with little programming skills had difficulties in becoming familiar with the toolkit. This is due to the fact that with the current implementation of our toolbox as a prerequisite basic knowledge of Unix, C, C++ and X 1 l/Motif is required. Particularly by the availability of well documented example programs the learning phase could be considerably shortened. Involved physicians had a lot of experience with the implementation of research ideas e.g. on modality consoles or workstations by use of a simple functions library written in FORTRAN. This served as the basis for efficiency evaluation. Due to the learning phase the development time was prolonged in the beginning. However, within a timeframe of three months it gradually decreased to between one half and one third of the time necessary for the traditional approach. Especially applications based on complex algorithms benefited from the available object classes because those hide implementation details from the programmer. With respect toflexibility we investigated whether all the research projects mentioned above could be comfortably implemented with the tool. Since our system is open and freely program-
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mable only few restrictions exist. These result from user interface consistency considerations. Due to the limitations of their traditional programming approach the clinical researchers had developed remarkable skills in finding workarounds. Therefore they did not feel restricted by the system architecture in any way. Usability refers to the adequacy of the workstation to be readily used within the clinical environment. Since clinical researchers usually cannot make an absolute clear distinction between routine work and research, an architecture providing routine functionality together with an extension toolbox found good acceptance. However, within the turnkey application system they missed some functions available on dedicated modality consoles. Although our system intends to support any modality it is difficult to provide the whole spectrum of modality specific functions on a single platform. Network integration and file transfer interfaces are other crucial factors which determine the usability of the system. In our current implementation images are transferred from the modalities to the workstation database via ethernet and FTP (file transfer protocol). This is not a comfortable but practical solution and for research applications seems to be sufficient. However, for routine clinical use a direct link to the modality patient and image databases is a prerequisite. This confronts us with a severe problem because manufacturers of imaging equipment seldom have a PACS (Picture Archiving and Communication System) interface or are reluctant to open it to third parties. Of particular value is the availability of an image10 object which allows for the interpretation of various image file formats. CLINICAL EXAMPLE: AN ADJUSTABLE DIGITAL BRAIN ATLAS IN NEURORADIOLOGY As mentioned in the previous chapter the platform has been used for the implementation of various clinical applications. As an example we will elaborate here on the digital brain atlas application. Here we use the Karolinska digital brain atlas (8) which we have integrated as part of the medical workstation database for the interpretation of positron emission tomography (PET) images, for multi-modality matching or for quantitative analysis of MRI or CT datasets as a knowledge base for automatic segmentation. From the computer science point of view the main problem consists of the matching of atlas structures to the individual patient anatomy and the visualization of the results. The realized approach encompasses mainly two steps. First, a rigid registration of the atlas with the 3D patient dataset is achieved by manual interaction. Changes of
Workstations for imaging and graphics research
transformation parameter,5 (translation, rotation, scaling) are immediately visualized on the workstation screen by a three-dimensional scene showing, for example, three orthogonal cuts through the patient volume with an integrated surface representation of the selected atlas structure (see Fig. 5). Second, an elastic matching procedure can be applied in order to exactly adjust the atlas by local deformations. Let us briefly explain how the medical workstation was used to realize this nevv application: We focus here on step one of the approach. Figure 6 illustrates the implementation mechanism. It gives a rough overview of the objects which have been used, their location within the overall system and the underlying dataflow concept. For reasons of caNmprehensiveness we ignore user interface related objects here. The turnkey application system allows patient images and atlas structures to be loaded from the database into the workstation’s main memory and to be displayed on the screen. The mesh and volumeset objects provide adequate datastructures together with methods to manipulate and access the data. The application is activated by mouse clicking the corresponding icon button within the menu field. It accesses patient as well as atlas data via the study handling interface. Get-voxel-set and get-mesh methods yield pointers to the voxelset and mesh ob-
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jects. Within the mesh object an atlas structure is represented as a triangulated surface description. This is transformed into a binary volume dataset by a voxelizer object. After each interactive modification of the transformation parameters which describe the spatial relation of the two datavolumes in a three-dimensional world coordinate system, a multi-modal 3D renderer is activated. This generates a 3D projection image (similar to Fig. 5) by simultaneously raycasting the two datavolumes and merging corresponding rays. The resulting image is stored within a picture object and given back to the turnkey system via the study handling interface. Here it is displayed and can be saved into the patient database or hardcopied. The implementation source code is short, because the voxelizer, voxelset, raycaster and picture objects already exist within the toolbox’s object class library. The application developer’s task was (a) to create a raymerger object; (b) to program the logical link between the objects used; and (c)to connect the user interface with the methods provided by the objects. Our evaluation results suggest that clinical research related to digital imaging and graphics benefits from the availability of the proposed toolkit system in three ways: First, the path from a research idea to its imple-
Fig. 5. 3D scene illustrating mesencephalon surface (dark) from a digital brain atlas matched to a magnetic resonance
patient dataset.
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Fig. 6. Object structure of the atlas-guided neuroradiological diagnosis application. A great amount of functionality is already provided by the turnkey application system.
mentation and evaluation is shortened. Second, the clinical availability of a variety of image processing and graphics methods motivates novel applications and the quick realization of new methods becomes possible. Third, the communication between clinical researchers and computer scientists is supported since the platform can be used as a medium for the presentation of ideas. However, the programming knowledge necessary to efficiently use our toolbox, has been an obstacle for addressing a broader community of clinical researchers. As a solution we propose a graphical programming interface which we know from commercial user interface builders or visual programming tools, such as AVS (Stardent Inc., Concord) and Explorer (Silicon Graphics, Mountain View). Its kernel will be a graphical object assembly editor allowing both, user interface objects and image analysis and synthesis objects to be selected and grouped together as an application specific object network on the workstation screen via mouse input. SUMMARY Today, the efficient use of computer platforms is of high relevance for the output of medical research in
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most clinical disciplines. The necessary knowledge and occupancy with computer science facts absorbs the attention of researchers from clinical issues. We tackle this problem by proposing an easy-to-use medical workstation system. This can be used as a tool for the efficient development of innovative applications in all clinical disciplines where digital images are acquired or used. The turnkey component of the system provides a great deal of ready-to-use functionality which is typically found as part of modality consoles. A graphical user interface simulating the look and feel of a conventional lightbox allows for an easy access to these methods. An integrated development toolbox enables researchers quickly to realize new ideas by assembly of already available software modules implemented as an object class library. The latter encompasses a variety of image processing and computer graphics methods grouped together with efficient data structures. It furthermore provides mechanisms to interface the turnkey workstation allowing new applications to be easily and consistently integrated and thus be linked to existing functionality. This is demonstrated by an application example: The graphically-interactive registration of a digital brain atlas with tomographic patient volumes. Our evaluation results suggest the extension of the toolbox by a visual programming editor for researchers who do not possess any programming skills. The described strategy avoids the problem of software heterogeneity and shortens the path of a new application into the clinical routine environment.
Acknowkedgmenfs-The
authors are grateful to Lennart Thrutjell,
Uppsala University, for his kind assistance of the digital brain atlas database.
with the implementation
REFERENCES 1. Upson, C.; Faulhaber, T.; Kamins, D.; Laidlaw, D.; Schlegel, D.; Vroom, J.; Gurwitz, R.; van Dam, A. The application visualization system: A computational environment for scientific visualization. IEEE Comput. Graph. Applications 9(4):30-42; 1989. 2. Dyer, D. S. A dataflow toolkit for visualization. IEEE Comput. Graph. and Applications 10:60-69, 1990. 3. Heffeman, P.; and Dekel, D. Imaging applications platform: Concept to implementation. In: Robb, R. A. ed. Bellingham: SPIE; Visualization Biomed. Comput. 1992:495-509. 4. Ho, B. K. T.; Ratib, 0.; and Hot-ii, S. C. PACS workstation design. Comput. Med. Imag. Graph. 15(3):147-155, 1991. 5. Staemmler, M.; Brill, R.; Becker, K.; Folkerts, K.-H.; and Gersonde, K. SUNRISE a software system for medical imaging analysis. In H. U. Lemke, M. L. Rhodes, C. C. Jaffe, and R. Felix, editors, Comput. Assist. Radiol., pages 671-677, Berlin, Heidelberg, New York, 1989. Springer. 6. Dahm, M.; Glaser, K.; Jansen-Dittmer, H.; Keizers, A.; Krueger, P.; Meyer-Ebrecht, D.; Miinker-Kaupp, K.; Rudolf, H.; Schilhng, C.; Sieslack, R.; Winkler, W.; Wein, B.; and Gunther, R. Ra-
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diologists start designing their digital workplace: prototyping with a digital image workstation in the radiology. In H. U. Lemke, M. L. Rhodes, C. C. Jafte, and R. Felix, editors, Comput. Assist. Radiol. pages 699-704, Berlin, Heidelberg, New York, 1991. Springer. 7. Ehricke, H.-H.; and &had, L. R. MRA-guided radiation treatment planning for cerebral angiomas. Comput. Med. Imag. Graph. 16(Z); 1992. 8. Greitz, T.; Holte, S.; Bohm, C.; Eriksson, L.; Seitz, R.; Ericson, K.; Nyblck, H.; and Stone-Elander, S. A database library as a diagnostic aid in neuroimaging. Neuroradiology 33(Suppl.):24, 1991.
EHRICKEreceived the MS. degree in medical informatics from the University of Heidelberg in 1988. In the same year he joined the Siemens Medical Engineering Group, Erlangen, as a research specialisl. in medical imaging. In 1991 he received his Ph.D. in computer science from the University of Heidelberg in collaboration with the German Cancer Research Center. In 1992 he joined the University of Tiibingen, Wilhelm-Schickard Institute for Informatics as an assistant professor for computer graphics and image processing. Since 1994 he holds the position of a professor at the Polytechnical University of Stralsund, Department of Electrical Engineering. His primary interest is in medical imaging, computer graphics and object-orimznted software engineering.
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degree in 1992. He is currently working on his Ph.D. in computer science at the WSI/GRIS computer graphics lab, University of Tiibingen, where he is focusing on research in the areas ofimage processing and application development systems for computer graphics in medicine. About the Author-THOMAS BUCK studied mechanical engineering at the Escola Polit&nica, Universidade Federal da Bahia, Brasil, where he received his B.Sc. in 1986. He received the M.Sc. in electrical engineering from the Faculdade de Engenharia El&ica, Universidade Estadual de Campinas, Brasil, in 1989. He is currently completing his Ph.D. in computer science at the WSI/GRIS computer graphics lab, University of Tiibingen, Germany. His research interests are digital image processing, computer graphics and artificial intelligence, and their application to medical sciences.
About the Author-HANS-HEINO
About the Author-THOMAS GRUNERT studied physics at the University of Tiibingen, Germany, where he received the BSc. and MSc.
About the Author-RUPERT KOLB studied Physics at the University of Tiibingen, Germany, where he received his M.Sc. in 199 I. He is currently a research assistant at the Department of Neuroradiology, University Hospitals of Tiibingen, working on a Ph.D. in computer science. His research interests include digital image processing, fast volume rendering and their applications to the neurosciences.
About the Author-MARTIN SKALEJ studied medicine at the University of Mainz, Germany, where he received his M.D. in 1986. Funded by the Deutsche Forschungsgemeinschaft he joined the University of Tiibingen in 1986 where he currently is a member of the Department of Neuroradiology. His major interests are magnetic resonance imaging, digital image processing, computer graphics and their application to the neurosciences.