Junko Ota

Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT

Kensuke Umehara, Junko Ota, Takayuki Ishida · Journal of Digital Imaging · 2017 · 206 citations

Computed Tomography, Super-resolution Imaging, Image Analysis +12

[Late phase II clinical study of RP56976 (docetaxel) in patients with advanced/recurrent gastric cancer: a Japanese Cooperative Study Group trial (group A)].

T Taguchi, Yuh Sakata, Rihito Kanamaru et al. · PubMed · 1998 · 86 citations

Oncology, Group A, Health Sciences +15

Super-resolution convolutional neural network for the improvement of the image quality of magnified images in chest radiographs

Kensuke Umehara, Junko Ota, Naoki Ishimaru et al. · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2017 · 33 citations

Engineering, Machine Learning, Srcnn Scheme +21

Super-Resolution Imaging of Mammograms Based on the Super-Resolution Convolutional Neural Network

Kensuke Umehara, Junko Ota, Takayuki Ishida · Open Journal of Medical Imaging · 2017 · 30 citations · Full text

Super-resolution Image Quality, High Resolution, Engineering +18

Deep Learning–based Post Hoc CT Denoising for Myocardial Delayed Enhancement

Tatsuya Nishii, Takuma Kobayashi, Hironori Tanaka et al. · Radiology · 2022 · 29 citations