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Automated identification of thoracic cage region from X-ray CT images
International Congress Series 1268 (2004) 1357
Automated identification of thoracic cage region from X-ray CT images Shinji Kobayashi *, Xiangrong Zhou, Takeshi Hara, Hiroshi Fujita, Ryujiro Yokoyama, Takuji Kiryu, Hiroaki Hoshi Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University, Yanagido 1-1, Gifu 501-1193, Japan
Keywords: Multi-slice CT image; Thoracic cage; Bone structure
1. Introduction During the development of a CAD system, identifications of internal organ regions are one of the important processes. In order to realize those processes, the thoracic cage region should be extracted firstly. In this paper, we propose a method of the automated identification of thoracic cages from three-dimensional (3-D) multislice CT images. 2. Method Our method tries to extract the thoracic cage region using the bone structure, because the extraction is simple, because it has high density, and because the shape is stable. This method estimates the initial shape of the thoracic cage using the bone frame, and then the thoracic cage region is extracted using an active contour model (ACM). This method is composed of five steps. First, we extract the bone structure from the 3-D CT images using various fundamental methods such as region growing approach. Second, we classify the bone structure into five parts (spine, sternum, rib, clavicle, and shoulder blade) based on the features of sharpness, the position, and the density. Third, we use them to form an initial shape of the thoracic cage. Fourth, we apply the ACM to trace the real contours of the cage region. Finally, we refine the contours and create the 3-D surface of the thoracic cage by the Bezier model. 3. Results and conclusion We applied this method to 11 patient cases of CT images and found that the thoracic cage region has been correctly extracted from 7 patient cases [1]. As next stage, we are still improving the proposed method and increasing the number of CT images to confirm the effectiveness of our method, and the results will be shown at the conference.
Reference [1] S. Kobayashi, et al., Development of Automated extraction method of thoracic cage in 3-D chest and torso CT images, CADM2003 03 (II)-10) (2003) 263 – 264 (in Japanese).
* Corresponding author. Tel.: +81-58-293-3151; fax: +81-58-293-3151. E-mail address: [email protected] (S. Kobayashi). 0531-5131/ D 2004 CARS and Elsevier B.V. All rights reserved. doi:10.1016/j.ics.2004.03.315
Automated identification of thoracic cage region from X-ray CT images Shinji Kobayashi *, Xiangrong Zhou, Takeshi Hara, Hiroshi Fujita, Ryujiro Yokoyama, Takuji Kiryu, Hiroaki Hoshi Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University, Yanagido 1-1, Gifu 501-1193, Japan
Keywords: Multi-slice CT image; Thoracic cage; Bone structure
1. Introduction During the development of a CAD system, identifications of internal organ regions are one of the important processes. In order to realize those processes, the thoracic cage region should be extracted firstly. In this paper, we propose a method of the automated identification of thoracic cages from three-dimensional (3-D) multislice CT images. 2. Method Our method tries to extract the thoracic cage region using the bone structure, because the extraction is simple, because it has high density, and because the shape is stable. This method estimates the initial shape of the thoracic cage using the bone frame, and then the thoracic cage region is extracted using an active contour model (ACM). This method is composed of five steps. First, we extract the bone structure from the 3-D CT images using various fundamental methods such as region growing approach. Second, we classify the bone structure into five parts (spine, sternum, rib, clavicle, and shoulder blade) based on the features of sharpness, the position, and the density. Third, we use them to form an initial shape of the thoracic cage. Fourth, we apply the ACM to trace the real contours of the cage region. Finally, we refine the contours and create the 3-D surface of the thoracic cage by the Bezier model. 3. Results and conclusion We applied this method to 11 patient cases of CT images and found that the thoracic cage region has been correctly extracted from 7 patient cases [1]. As next stage, we are still improving the proposed method and increasing the number of CT images to confirm the effectiveness of our method, and the results will be shown at the conference.
Reference [1] S. Kobayashi, et al., Development of Automated extraction method of thoracic cage in 3-D chest and torso CT images, CADM2003 03 (II)-10) (2003) 263 – 264 (in Japanese).
* Corresponding author. Tel.: +81-58-293-3151; fax: +81-58-293-3151. E-mail address: [email protected] (S. Kobayashi). 0531-5131/ D 2004 CARS and Elsevier B.V. All rights reserved. doi:10.1016/j.ics.2004.03.315