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A study on the three-dimensional image processing method for 3DX Multi Image Micro CT
International Congress Series 1230 (2001) 706 – 712
A study on the three-dimensional image processing method for 3DX Multi Image Micro CT Shinobu Befua,*, Hitoshi Tsunashimaa, Yoshinori Araib a
Department of Mechanical Engineering, College of Industrial Technology, Nihon University, 1-2-1 Izumi-cho Narashinoshi, Chiba 275-8575, Japan b Department of Radiology, Nihon University School of Dentistry, Chioda-ku, Tokyo 101-8310, Japan
Abstract Objective: A clinical model of limited cone-beam X-ray CT (3DX Multi Image Micro CT) has been developed by Arai et al. [Y. Arai, E. Tammisalo, K. Iwai, K. Hashimoto, K. Shinoda, Development of ortho cubic super high resolution CT (Ortho-CT), Car ’98 Computer-Assisted Radiology and Surgery, Elsevier, Amsterdam, 1998, pp. 780 – 785] for dental use. In this paper, a three-dimensional image processing method for 3DX Multi Image Micro CT (3DX), which is capable of obtaining clear three-dimensional images, is proposed. Method: First of all, the three-dimensional projection data are decomposed to a set of two-dimensional data. However, the obtained data contain much noise because the projection data are obtained by low-level X-ray. Therefore, we proposed the following steps for obtaining clear three-dimensional images. Firstly, contrast stretching is applied to the set of two-dimensional image data based on the contrast information of the target image for avoiding noise. Then, the edge detection with the Canny operator is performed. In our method, the loss of the target image, which is caused by noise reduction and edge detection, can be interpolated by the image obtained from different directions. Finally, the clear edge of the two-dimensional image data is reconstructed to the three-dimensional image data. Result: It is shown that clear threedimensional images are obtained when we applied the proposed method for three-dimensional imaging of the temporomandibular joint. Conclusion: A new method for constructing threedimensional images from the image data obtained from limited cone-beam-type X-ray CT is proposed. The effectiveness of the proposed method is shown by constructing three-dimensional images of the temporomandibular joint. D 2001 Elsevier Science B.V. All rights reserved. Keywords: CT; X-ray; Cone beam; Dental; Edge detection; Image processing
*
Corresponding author. Tel.: +81-47-474-2339; fax: +81-47-474-2349. E-mail address: [email protected] (S. Befu).
0531-5131/01/$ – see front matter D 2001 Elsevier Science B.V. All rights reserved. PII: S 0 5 3 1 - 5 1 3 1 ( 0 1 ) 0 0 11 6 - 9
S. Befu et al. / International Congress Series 1230 (2001) 706–712
707
1. Introduction With the development of computer technology, diagnosis using three-dimensional imaging is carried out in dentistry. Arai et al. [1] have developed a clinical model of limited cone-beam X-ray CT (3DX Multi Image Micro CT) for dental use, with J. Morita Mfg. Corp. (Kyoto Japan), and started to use the model in clinical practice. The threedimensional image display program for 3DX experimental model (‘‘Ortho-CT’’) is developed [2] and applied. However, the obtained three-dimensional image is not satisfactory because it contains much noise or there is a loss of original data. In this paper, a new three-dimensional image processing method for 3DX, which is capable of obtaining clear three-dimensional images, is proposed. As an application example, the results for constructing three-dimensional images of the temporomandibular joint are shown.
2. Materials and methods Firstly, as shown in Fig. 1, the temporomandibular joint of the human body with the phantom is scanned by 3DX, and three-dimensional projection data are obtained. The obtained data are heights of 240 voxels (about 30 mm) and 300 voxels (about 40 mm) in diameter. Fig. 2 shows a three-dimensional image obtained by using the conventional method. We can see from the figure that the original surface data are lost as a result of reducing noise. The three-dimensional projection data are first decomposed to a set of two-dimensional images. Then, three-dimensional projection data are broached from multi-directions as shown in Fig. 3. In our method, the loss of the target image, which is caused by noise reduction and edge detection, can be interpolated by the image obtained from different directions. As the image broached in 1-voxel interval contains the noise (see Fig. 4), the simple noise reduction with a moving average of 8-voxel interval is applied (see Fig. 5). As a result, it can be seen from Fig. 6 that noise reduction can be performed.
Fig. 1. Overview of ‘‘the 3DX’’ and phantom.
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Fig. 2. Three-dimensional image by the conventional method.
Fig. 3. Extraction of the images.
Fig. 4. Two-dimensional image (1 voxel).
S. Befu et al. / International Congress Series 1230 (2001) 706–712
Fig. 5. Moving average images.
Fig. 6. Two-dimensional image (8 voxels).
Fig. 7. Preprocessing images.
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Fig. 8. Three-dimensional images in broaching from one direction.
The two-dimensional image processing is carried out through the following steps. Firstly, contrast stretching is applied to the set of two-dimensional image data based on the contrast information of the target (left of Fig. 7). Then, edge detection with the Canny operator [3] is performed (right of Fig. 7). The method is applied to 276 sheets in one direction. The interpolation with 16 directions indicates that 4416 sheets are dealt with. Finally, the clear edge of the two-dimensional image data is reconstructed to the threedimensional image.
3. Results and discussion The three-dimensional images constructed only from 0° and 90° directions are shown in Fig. 8. We can see that a hole appeared at Nos. 1 and 2 in case A; however, it did not appear at the same point in case B. On the contrary, the hole at No. 3 in case B did not appear at the same point in case A. This fact indicates that the hole can be interpolated by the image of orthogonal direction. Next, case A + case B images are shown in Fig. 9.
Fig. 9. Three-dimensional images in broaching from two directions.
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Fig. 10. Three-dimensional images obtained by multi-directional interpolation.
The holes are reduced at Nos. 1, 2 and 3, but there are some holes at No. 4. Then, Fig. 10 shows the three-dimensional images of the temporomandibular joint constructed with the multi-directional interpolation (16 directions). It should be noted that holes (for example, No. 4), which represent the loss of original data, are completely fixed by the proposed method. The reduction of noise in the two-dimensional image causes the loss of the edge. The essential part of the proposed method is that the clear edge data are obtained by multidirectional interpolation instead of complex image processing. It is shown that our method is effective for constructing three-dimensional images based on noisy three-dimensional projection data, which are obtained from 3DX Multi Image Micro CT. The proposed method is quite simple because it does not require any complex image processing methods that are often used in CT or MRI images.
4. Conclusion A new method for constructing three-dimensional images from the image data obtained from 3DX Multi Image Micro CT is proposed. The effectiveness of the
712
S. Befu et al. / International Congress Series 1230 (2001) 706–712
proposed method is shown by constructing three-dimensional images of the temporomandibular joint. The application of the proposed method to the data obtained from actual patient is now planned.
References [1] Y. Arai, E. Tammisalo, K. Iwai, K. Hashimoto, K. Shinoda, Development of ortho cubic super high resolution CT (Ortho-CT), Car ’98 Computer-Assisted Radiology and Surgery, Elsevier, Amsterdam, 1998, pp. 780 – 785. [2] Y. Arai, et al., Development of 3-D surface display program for limited cone beam CT (Ortho-CT), Oral and maxillofacial radiology today, Proceedings of the 12th DMFR, Elsevier, Amsterdam, 2000, pp. 108 – 112. [3] C. John, A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8 (6) (1986) 679 – 698 (November).
A study on the three-dimensional image processing method for 3DX Multi Image Micro CT Shinobu Befua,*, Hitoshi Tsunashimaa, Yoshinori Araib a
Department of Mechanical Engineering, College of Industrial Technology, Nihon University, 1-2-1 Izumi-cho Narashinoshi, Chiba 275-8575, Japan b Department of Radiology, Nihon University School of Dentistry, Chioda-ku, Tokyo 101-8310, Japan
Abstract Objective: A clinical model of limited cone-beam X-ray CT (3DX Multi Image Micro CT) has been developed by Arai et al. [Y. Arai, E. Tammisalo, K. Iwai, K. Hashimoto, K. Shinoda, Development of ortho cubic super high resolution CT (Ortho-CT), Car ’98 Computer-Assisted Radiology and Surgery, Elsevier, Amsterdam, 1998, pp. 780 – 785] for dental use. In this paper, a three-dimensional image processing method for 3DX Multi Image Micro CT (3DX), which is capable of obtaining clear three-dimensional images, is proposed. Method: First of all, the three-dimensional projection data are decomposed to a set of two-dimensional data. However, the obtained data contain much noise because the projection data are obtained by low-level X-ray. Therefore, we proposed the following steps for obtaining clear three-dimensional images. Firstly, contrast stretching is applied to the set of two-dimensional image data based on the contrast information of the target image for avoiding noise. Then, the edge detection with the Canny operator is performed. In our method, the loss of the target image, which is caused by noise reduction and edge detection, can be interpolated by the image obtained from different directions. Finally, the clear edge of the two-dimensional image data is reconstructed to the three-dimensional image data. Result: It is shown that clear threedimensional images are obtained when we applied the proposed method for three-dimensional imaging of the temporomandibular joint. Conclusion: A new method for constructing threedimensional images from the image data obtained from limited cone-beam-type X-ray CT is proposed. The effectiveness of the proposed method is shown by constructing three-dimensional images of the temporomandibular joint. D 2001 Elsevier Science B.V. All rights reserved. Keywords: CT; X-ray; Cone beam; Dental; Edge detection; Image processing
*
Corresponding author. Tel.: +81-47-474-2339; fax: +81-47-474-2349. E-mail address: [email protected] (S. Befu).
0531-5131/01/$ – see front matter D 2001 Elsevier Science B.V. All rights reserved. PII: S 0 5 3 1 - 5 1 3 1 ( 0 1 ) 0 0 11 6 - 9
S. Befu et al. / International Congress Series 1230 (2001) 706–712
707
1. Introduction With the development of computer technology, diagnosis using three-dimensional imaging is carried out in dentistry. Arai et al. [1] have developed a clinical model of limited cone-beam X-ray CT (3DX Multi Image Micro CT) for dental use, with J. Morita Mfg. Corp. (Kyoto Japan), and started to use the model in clinical practice. The threedimensional image display program for 3DX experimental model (‘‘Ortho-CT’’) is developed [2] and applied. However, the obtained three-dimensional image is not satisfactory because it contains much noise or there is a loss of original data. In this paper, a new three-dimensional image processing method for 3DX, which is capable of obtaining clear three-dimensional images, is proposed. As an application example, the results for constructing three-dimensional images of the temporomandibular joint are shown.
2. Materials and methods Firstly, as shown in Fig. 1, the temporomandibular joint of the human body with the phantom is scanned by 3DX, and three-dimensional projection data are obtained. The obtained data are heights of 240 voxels (about 30 mm) and 300 voxels (about 40 mm) in diameter. Fig. 2 shows a three-dimensional image obtained by using the conventional method. We can see from the figure that the original surface data are lost as a result of reducing noise. The three-dimensional projection data are first decomposed to a set of two-dimensional images. Then, three-dimensional projection data are broached from multi-directions as shown in Fig. 3. In our method, the loss of the target image, which is caused by noise reduction and edge detection, can be interpolated by the image obtained from different directions. As the image broached in 1-voxel interval contains the noise (see Fig. 4), the simple noise reduction with a moving average of 8-voxel interval is applied (see Fig. 5). As a result, it can be seen from Fig. 6 that noise reduction can be performed.
Fig. 1. Overview of ‘‘the 3DX’’ and phantom.
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S. Befu et al. / International Congress Series 1230 (2001) 706–712
Fig. 2. Three-dimensional image by the conventional method.
Fig. 3. Extraction of the images.
Fig. 4. Two-dimensional image (1 voxel).
S. Befu et al. / International Congress Series 1230 (2001) 706–712
Fig. 5. Moving average images.
Fig. 6. Two-dimensional image (8 voxels).
Fig. 7. Preprocessing images.
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Fig. 8. Three-dimensional images in broaching from one direction.
The two-dimensional image processing is carried out through the following steps. Firstly, contrast stretching is applied to the set of two-dimensional image data based on the contrast information of the target (left of Fig. 7). Then, edge detection with the Canny operator [3] is performed (right of Fig. 7). The method is applied to 276 sheets in one direction. The interpolation with 16 directions indicates that 4416 sheets are dealt with. Finally, the clear edge of the two-dimensional image data is reconstructed to the threedimensional image.
3. Results and discussion The three-dimensional images constructed only from 0° and 90° directions are shown in Fig. 8. We can see that a hole appeared at Nos. 1 and 2 in case A; however, it did not appear at the same point in case B. On the contrary, the hole at No. 3 in case B did not appear at the same point in case A. This fact indicates that the hole can be interpolated by the image of orthogonal direction. Next, case A + case B images are shown in Fig. 9.
Fig. 9. Three-dimensional images in broaching from two directions.
S. Befu et al. / International Congress Series 1230 (2001) 706–712
711
Fig. 10. Three-dimensional images obtained by multi-directional interpolation.
The holes are reduced at Nos. 1, 2 and 3, but there are some holes at No. 4. Then, Fig. 10 shows the three-dimensional images of the temporomandibular joint constructed with the multi-directional interpolation (16 directions). It should be noted that holes (for example, No. 4), which represent the loss of original data, are completely fixed by the proposed method. The reduction of noise in the two-dimensional image causes the loss of the edge. The essential part of the proposed method is that the clear edge data are obtained by multidirectional interpolation instead of complex image processing. It is shown that our method is effective for constructing three-dimensional images based on noisy three-dimensional projection data, which are obtained from 3DX Multi Image Micro CT. The proposed method is quite simple because it does not require any complex image processing methods that are often used in CT or MRI images.
4. Conclusion A new method for constructing three-dimensional images from the image data obtained from 3DX Multi Image Micro CT is proposed. The effectiveness of the
712
S. Befu et al. / International Congress Series 1230 (2001) 706–712
proposed method is shown by constructing three-dimensional images of the temporomandibular joint. The application of the proposed method to the data obtained from actual patient is now planned.
References [1] Y. Arai, E. Tammisalo, K. Iwai, K. Hashimoto, K. Shinoda, Development of ortho cubic super high resolution CT (Ortho-CT), Car ’98 Computer-Assisted Radiology and Surgery, Elsevier, Amsterdam, 1998, pp. 780 – 785. [2] Y. Arai, et al., Development of 3-D surface display program for limited cone beam CT (Ortho-CT), Oral and maxillofacial radiology today, Proceedings of the 12th DMFR, Elsevier, Amsterdam, 2000, pp. 108 – 112. [3] C. John, A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8 (6) (1986) 679 – 698 (November).