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Nobuhiko Sugano

Department of Orthopaedic Medical Engineering, Osaka University Graduate School of Medicine, Suita city, Japan

Automated segmentation of an intensity calibration phantom in clinical CT images using a convolutional neural network

Dec 21, 2020
Keisuke Uemura, Yoshito Otake, Masaki Takao, Mazen Soufi, Akihiro Kawasaki, Nobuhiko Sugano, Yoshinobu Sato

* 29 pages, 7 figures. The source code and the model used for segmenting the phantom are open and can be accessed via 

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Region-based Convolution Neural Network Approach for Accurate Segmentation of Pelvic Radiograph

Oct 29, 2019
Ata Jodeiri, Reza A. Zoroofi, Yuta Hiasa, Masaki Takao, Nobuhiko Sugano, Yoshinobu Sato, Yoshito Otake

* Accepted at ICBME 2019 

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Estimation of Pelvic Sagittal Inclination from Anteroposterior Radiograph Using Convolutional Neural Networks: Proof-of-Concept Study

Oct 26, 2019
Ata Jodeiri, Yoshito Otake, Reza A. Zoroofi, Yuta Hiasa, Masaki Takao, Keisuke Uemura, Nobuhiko Sugano, Yoshinobu Sato

* Best Technical Paper Award Winner of CAOS 2018 (

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Automated Muscle Segmentation from Clinical CT using Bayesian U-Net for Personalization of a Musculoskeletal Model

Jul 21, 2019
Yuta Hiasa, Yoshito Otake, Masaki Takao, Takeshi Ogawa, Nobuhiko Sugano, Yoshinobu Sato

* 11 pages, 10 figures, and supplementary materials 

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Automated Segmentation of Hip and Thigh Muscles in Metal Artifact-Contaminated CT using Convolutional Neural Network-Enhanced Normalized Metal Artifact Reduction

Jun 27, 2019
Mitsuki Sakamoto, Yuta Hiasa, Yoshito Otake, Masaki Takao, Yuki Suzuki, Nobuhiko Sugano, Yoshinobu Sato

* 7 pages, 5 figures 

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Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data size

Jul 31, 2018
Yuta Hiasa, Yoshito Otake, Masaki Takao, Takumi Matsuoka, Kazuma Takashima, Jerry L. Prince, Nobuhiko Sugano, Yoshinobu Sato

* 10 pages, 7 figures, MICCAI 2018 Workshop on Simulation and Synthesis in Medical Imaging 

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