Development of an automated method for the detection of chronic lacunar infarct regions in brain MR images

IEICE Transactions on Information and Systems

Volumn E90-D, Issue 6, 2007, Pages 943-954

  Yokoyama, Ryujiro ^a   Zhang, Xuejun ^a,b   Uchiyama, Yoshikazu ^a   Fujita, Hiroshi ^a   Hara, Takeshi ^a   Zhou, Xiangrong ^a   Kanematsu, Masayuki ^a   Asano, Takahiko ^a   Kondo, Hiroshi ^a   Goshima, Satoshi ^a   Hoshi, Hiroaki ^a   Iwama, Toru ^a  

^a GIFU UNIVERSITY   (Japan)

^b GUANGXI UNIVERSITY   (China)

Author keywords

Brain mri; Computer aided diagnosis; Lacunar infarct; Mathematical morphology; T1 and t2 weighted images

Indexed keywords

AUTOMATION; DIAGNOSIS; MAGNETIC LEVITATION VEHICLES; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MORPHOLOGY; MEDICAL COMPUTING;

AUTOMATED IDENTIFICATION; BRAIN MRI; COMPUTER AIDED DETECTION SYSTEMS; LACUNAR INFARCT; MORPHOLOGICAL OPENING; REGION-GROWING TECHNIQUES; SENSITIVITY AND SPECIFICITY; T2 WEIGHTED;

COMPUTER AIDED DIAGNOSIS;

EID: 38049041281     PISSN: 09168532     EISSN: 17451361     Source Type: Journal    
DOI: 10.1093/ietisy/e90-d.6.943     Document Type: Article

References (24)

1. Y. Shinohara, "Significance and the present conditions of brain detection survey (Brain Doc)," The Journal of the Japanese Society of Internal Medicine, vol. 86, pp. 787-791, 1997.
2. C. M. Fisher, "Lacunes: Small, deep cerebral infarcts," Neurology, vol. 15, pp. 774-784, 1965.
3. T. Sawada, "What is the asymptopmatic brain vessel disease-The definition and diagnosis basis," The Journal of the Japanese Society of Internal Medicine, vol. 86, pp. 725-732, 1997.
4. S. Kobayashi, "MRI and health screening of the brain: Asymptomatic cerebral infarction," Japanese Journal of Diagnostic Imaging, vol. 17, no. 2, pp. 159-167, 1998.
5. S. Kobayashi, H. Koide, and H. Bokura, "Prospective study on stroke onset in silent cerebral infarction," J. Stroke and Cerebrovascular Diseases, vol. 6, pp. 100-105, 1996.
6. H. Kou, H. Suzuki, and J. Toriwaki, "Automated segmentation of MRI head images by 3-D region growing method which utilizes edge information," Transactions of the Japanese Society for Medical and Biological Engineering, vol. 29, no. 3, pp. 170-177, 1991.
7. N. Hayashi, S. Sanada, M. Suzuki, and Y. Matsuura, "Segmentation method of the cerebellum and brainstem on MR images using mathematical morphology," Medical Imaging and Information Sciences, vol. 21, no. 1, pp. 109-115, 2004.
8. K. Van Leemput, F. Maes, D. Vandermeulen, and P. Suetens, "Automated model-based tissue classification of MR images of the brain," IEEE Trans. Med. Imaging, vol. 18, no. 10, pp. 897-908, 1999.
9. I. Uwano, K. Fujiwara, K. Matsuda, M. Kameda, A. Doi, T. Inoue, and A. Ogawa, "An extraction of a brain tumor area from MRI images using 3D region growing," IEICE Technical Report, MI 2002-73, 2002.
10. D. L. Wilson and J. A. Nobel, "Segmentation of cerebral vessels and aneurysms from MR angiography data," Lect. Notes Comput. Sci., vol. 1230, pp. 423-428, 1997.
11. D. L. Wilson and J. A. Nobel, "An adaptive segmentation algorithm for time-of-flight MRA data," IEEE Trans. Med. Imaging, vol. 18, no. 10, pp. 938-945, 1999.
12. H. Arimura, Q. Li, Y. Korogi, T. Hirai, H. Abe, Y. Yamashita, S. Katsuragawa, R. Ikeda, and K. Doi, "Automated computerized scheme for detection of unruptured intracranial aneurysms in threedimensional MRA," Acad. Radiol., vol. 11, pp. 1093-1104, 2004.
13. T. Hirai, Y. Korogi, H. Arimura, S. Katsuragawa, M. Kitajima, M. Yamura, Y. Yamashita, and K. Doi, "Intracranial aneurysms at MR angiography: Effect of computer-aided diagnosis on radiologists' detection performance," Radiology, vol. 237, pp. 605-610, 2005.
14. Y. Uchiyama, H. Ando, R. Yokoyama, T. Hara, H. Fujita, and T. Iwama, "Computer-aided diagnosis scheme for detection of unruptured intracranial aneurysms in MR angiography," Proc. 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, paper #296, 2005.
15. H. Arimura, Q. Li, Y. Korogi, T. Hirai, S. Katsuragawa, Y. Yamoshita, K. Tsuchida, and K. Doi, "Computerized detection of intracranial aneurysms for three-dimensional MR angiography: Feature extraction of small protrusions bases on a shape-based difference image technique," Med. Phys., vol. 33, no. 2, pp. 394-401, 2006.
16. N. Hayashi, Y. Matsutani, T. Matsumoto, H. Mori, A. Kunimatsu, O. Abe, S. Aoki, K. Ohtomo, N. Takano, and K. Matsumoto, "Feasibility of a curvature-based enhanced display system for detecting cerebral aneurysms in MR angiography," Magnetic Resonance in Medical Scienece, vol. 2, pp. 29-36, 2003.
17. S. Kobayashi, K. Kondo, and Y. Hata, "Computer-aided diagnosis of intracranial aneurysms in MRA images with case-based resoning," IEICE Trans. Inf. & Syst., vol. E89-D, no. 1, pp. 340-350, Jan. 2006.
18. R. Yokoyama, Y. Lee, T. Hara, H. Fujita, T. Asano, H. Hoshi, T. Iwama, and N. Sakai, "An automated detection of lacunar infarct regions in brain MR images: Preliminary study," Japanese Journal of Radiological Technology, vol. 50, no. 3, pp. 399-405, 2002.
19. T. Araki, ed., A Key to MRI Interpretation, pp. 40-41, Shujunsha, Tokyo, 1995.
20. N. Otsu, "Discriminant and least square threshold selection," Proc. 4IJCPR, pp. 592-596, 1978.
21. J. Kittler and J. Illingworth, "On threshold selection using clustering criteria," IEEE Trans. Syst. Man Cybern., vol. 15, no. 5, pp. 652-655, 1985.
22. A. Koto, Y. Hashimoto, H. Tougi, and Y. Fukuuchi, Brain and Circulation, vol. 6, no. 2, pp. 11-23, 2001.
23. W. T. Longstreth Jr, T. A. Manolio, and A. Arnold, "Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly: The cardiovascular health study," Stroke, vol. 27, pp. 1274-1282, 1996.
24. A. Nagazumi, M. Takahashi, and Y. Ktayama, "Medical treatment of silent lacuna stroke," Brain and Circulation, vol. 6, no. 2, pp. 39-40, 2001.