Presentation | 2018-03-20 [Short Paper] Prostate Zonal Segmentation Using Deep Learning Changhee Han, Jin Zhang, Ryuichiro Hataya, Yudai Nagano, Hideki Nakayama, Leonardo Rundo, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Prostate cancer is the second most common cancer among men and segmenting the Transition Zone (TZ) and Peripheral Zone (PZ) of the prostate is clinically essential as the frequency and severity of tumors can differ in these zones; however, the boundary of them are unclear. Therefore, we automatically segment those zones on T2-weighted Magnetic Resonance (MR) images using deep learning. Here, we use two different prostate datasets to confirm the influence of concatenating different datasets towards better clinical diagnosis. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Prostate Zonal SegmentationDeep LearningSegNetMRI |
Paper # | MI2017-86 |
Date of Issue | 2018-03-12 (MI) |
Conference Information | |
Committee | SIP / EA / SP / MI |
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Conference Date | 2018/3/19(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics [SIP, EA, SP]/ Medical Image Engineering, Analysis, Recognition, etc. [MI] |
Chair | Masahiro Okuda(Univ. of Kitakyushu) / Suehiro Shimauchi(NTT) / Yoichi Yamashita(Ritsumeikan Univ.) / Kensaku Mori(Nagoya Univ.) |
Vice Chair | Shogo Muramatsu(Niigata Univ.) / Naoyuki Aikawa(TUS) / Mitsunori Mizumachi(Kyutech) / Hiroki Mori(Utsunomiya Univ.) / Yoshiki Kawata(Tokushima Univ.) / Yuichi Kimura(Kinki Univ.) |
Secretary | Shogo Muramatsu(Chiba Inst. of Tech.) / Naoyuki Aikawa(Takushoku Univ.) / Mitsunori Mizumachi(Akita Pref. Univ.) / Hiroki Mori(Shizuoka Inst. of Science and Tech.) / Yoshiki Kawata(Shizuoka Univ.) / Yuichi Kimura(Meijo Univ.) |
Assistant | Masayoshi Nakamoto(Hiroshima Univ.ひろ) / TREVINO Jorge(Tohoku Univ.) / Nobutaka Ito(NTT) / Kei Hashimoto(Nagoya Inst. of Tech.) / Satoshi Kobashikawa(NTT) / Ryo Haraguchi(Univ. of Hyogo) / Yasushi Hirano(Yamaguchi Univ.) |
Paper Information | |
Registration To | Technical Committee on Signal Processing / Technical Committee on Engineering Acoustics / Technical Committee on Speech / Technical Committee on Medical Imaging |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | [Short Paper] Prostate Zonal Segmentation Using Deep Learning |
Sub Title (in English) | |
Keyword(1) | Prostate Zonal SegmentationDeep LearningSegNetMRI |
1st Author's Name | Changhee Han |
1st Author's Affiliation | The University of Tokyo(Univ. of Tokyo) |
2nd Author's Name | Jin Zhang |
2nd Author's Affiliation | The University of Tokyo(Univ. of Tokyo) |
3rd Author's Name | Ryuichiro Hataya |
3rd Author's Affiliation | The University of Tokyo(Univ. of Tokyo) |
4th Author's Name | Yudai Nagano |
4th Author's Affiliation | The University of Tokyo(Univ. of Tokyo) |
5th Author's Name | Hideki Nakayama |
5th Author's Affiliation | The University of Tokyo(Univ. of Tokyo) |
6th Author's Name | Leonardo Rundo |
6th Author's Affiliation | Milano-Bicocca University(Milano-Bicocca Univ.) |
Date | 2018-03-20 |
Paper # | MI2017-86 |
Volume (vol) | vol.117 |
Number (no) | MI-518 |
Page | pp.pp.69-70(MI), |
#Pages | 2 |
Date of Issue | 2018-03-12 (MI) |