| Presentation | 2007-09-20 Development of automated method for detection of multiple sclerosis candidate regions based on brain magnetic resonance images Daisuke Yamamoto, Hidetaka Arimura, Shingo Kakeda, Yasuo Yamashita, Seiji Kumazawa, Fukai Toyofuku, Yoshiharu Higashida, Yukunori Korogi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The severity and symptom of multiple sclerosis (MS) depend on its location, shape, and area. It is very important to evaluate the temporal change of MS regions in terms of location, shape, and area for estimation of MS progression. Our aim of this study was to develop an automated method for detection of MS candidate regions based on three types of brain magnetic resonance (MR) images, i.e., T1-, T2-weighted images, and fluid attenuated inversion-recovery (FLAIR) images. The MS candidate regions were identified based on a multiple gray level thresholding technique and a region growing technique on a subtraction image between a T1-image and a FLAIR image. The candidate regions were determined by monitoring the interval changes of image feature values for region growing based on pixel value. Eight image features were determined for each candidate region, and many false positive regions were removed by using simple rules and a support vector machine (SVM). We applied our method to 24 slices of four MS cases, which included 80 MS regions. As a result, 87.5% of MS regions were detected without false positives per slice. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | computer-aided diagnosis (CAD) / multiple sclerosis (MS) / magnetic resonance imaging (MRI) / image feature analysis |
| Paper # | MI2007-45 |
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| Conference Information | |
| Committee | MI |
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| Conference Date | 2007/9/13(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Medical Imaging (MI) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Development of automated method for detection of multiple sclerosis candidate regions based on brain magnetic resonance images |
| Sub Title (in English) | |
| Keyword(1) | computer-aided diagnosis (CAD) |
| Keyword(2) | multiple sclerosis (MS) |
| Keyword(3) | magnetic resonance imaging (MRI) |
| Keyword(4) | image feature analysis |
| 1st Author's Name | Daisuke Yamamoto |
| 1st Author's Affiliation | Kyushu University() |
| 2nd Author's Name | Hidetaka Arimura |
| 2nd Author's Affiliation | Kyushu University |
| 3rd Author's Name | Shingo Kakeda |
| 3rd Author's Affiliation | University of Occupational and Environmental Health |
| 4th Author's Name | Yasuo Yamashita |
| 4th Author's Affiliation | Kyushu University Hospital |
| 5th Author's Name | Seiji Kumazawa |
| 5th Author's Affiliation | Kyushu University |
| 6th Author's Name | Fukai Toyofuku |
| 6th Author's Affiliation | Kyushu University |
| 7th Author's Name | Yoshiharu Higashida |
| 7th Author's Affiliation | Kyushu University |
| 8th Author's Name | Yukunori Korogi |
| 8th Author's Affiliation | University of Occupational and Environmental Health |
| Date | 2007-09-20 |
| Paper # | MI2007-45 |
| Volume (vol) | vol.107 |
| Number (no) | 220 |
| Page | pp.pp.- |
| #Pages | 2 |
| Date of Issue | |