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Ulas Bagci | Sachin Jambawalikar | Naji Khosravan | Yucheng Liu | Joseph N. Stember | Yulin Liu | Jonathan Shoag
[1] 拓海 杉山,et al. “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .
[2] M van Herk,et al. Definition of the prostate in CT and MRI: a multi-observer study. , 1999, International journal of radiation oncology, biology, physics.
[3] Wendy L. Smith,et al. Prostate volume contouring: a 3D analysis of segmentation using 3DTRUS, CT, and MR. , 2007, International journal of radiation oncology, biology, physics.
[4] Christopher Joseph Pal,et al. The Importance of Skip Connections in Biomedical Image Segmentation , 2016, LABELS/DLMIA@MICCAI.
[5] Jan Kautz,et al. Loss Functions for Image Restoration With Neural Networks , 2017, IEEE Transactions on Computational Imaging.
[6] Ninon Burgos,et al. Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning , 2017, Physics in medicine and biology.
[7] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[8] Jelmer M. Wolterink,et al. Deep MR to CT Synthesis Using Unpaired Data , 2017, SASHIMI@MICCAI.
[9] Martin Eklund,et al. Prostate-specific antigen (PSA) density in the diagnostic algorithm of prostate cancer , 2017, Prostate Cancer and Prostatic Diseases.
[10] Indrin J Chetty,et al. Automatic Segmentation of the Prostate on CT Images Using Deep Neural Networks (DNN). , 2019, International journal of radiation oncology, biology, physics.
[11] Anant Madabhushi,et al. Concurrent segmentation of the prostate on MRI and CT via linked statistical shape models for radiotherapy planning. , 2012, Medical physics.