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Original Articles

The use of an active appearance model for automated prostate segmentation in magnetic resonance

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Pages 1374-1377 | Received 31 May 2013, Accepted 30 Jun 2013, Published online: 05 Sep 2013

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Takafumi Nemoto, Natsumi Futakami, Etsuo Kunieda, Masamichi Yagi, Atsuya Takeda, Takeshi Akiba, Eride Mutu & Naoyuki Shigematsu. (2021) Effects of sample size and data augmentation on U-Net-based automatic segmentation of various organs. Radiological Physics and Technology 14:3, pages 318-327.
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Takafumi Nemoto, Natsumi Futakami, Masamichi Yagi, Etsuo Kunieda, Takeshi Akiba, Atsuya Takeda & Naoyuki Shigematsu. (2020) Simple low-cost approaches to semantic segmentation in radiation therapy planning for prostate cancer using deep learning with non-contrast planning CT images. Physica Medica 78, pages 93-100.
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Anne Sofie Korsager, Valerio Fortunati, Fedde van der Lijn, Jesper Carl, Wiro Niessen, Lasse Riis Østergaard & Theo van Walsum. (2015) The use of atlas registration and graph cuts for prostate segmentation in magnetic resonance images. Medical Physics 42:4, pages 1614-1624.
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