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RISS 인기검색어
- 검색키워드
- 저자 : Takao Ino (검색결과 2 건)
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- 유료
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Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method
Masami Goto,Osamu Abe,Tosiaki Miyati,Hiroyuki Kabasawa,Hidemasa Takao,Naoto Hayashi,Tomomi Kurosu,Takeshi Iwatsubo,Fumio Yamashita,Hiroshi Matsuda,Harushi Mori,Akira Kunimatsu,Shigeki Aoki,Kenji Ino,K 대한영상의학회 2012 Korean Journal of Radiology Vol.13 No.4
Objective: Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Materials and Methods: Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 x [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. Results: A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. Conclusion: The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials. Objective: Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Materials and Methods: Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 x [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. Results: A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. Conclusion: The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials.
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Guidelines for Human Interface Design of Rescue Robots
Yasuyoshi Yokokohji,Takashi Tubouchi,Akichika Tanaka,Tomoaki Yoshida,Eiji Koyangi,Fumitoshi Matsuno,Shigeo Hirose,Hiroyuki Kuwahara,Fumiaki Takemura,Takao Ino,Kensuk Takita,Naoji Shiroma,Tetsushi Kame 제어로봇시스템학회 2006 제어로봇시스템학회 국제학술대회 논문집 Vol.2006 No.10
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