Tomoki Uemura

According to our database, Tomoki Uemura authored at least 15 papers between 2017 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Weakly unsupervised conditional generative adversarial network for image-based prognostic prediction for COVID-19 patients based on chest CT.

Tomoki Uemura, Janne J. Näppi, Chinatsu Watari, Toru Hironaka, Tohru Kamiya, Hiroyuki Yoshida

Medical Image Anal., 2021

A generative flow-based model for volumetric data augmentation in 3D deep learning for computed tomographic colonography.

Tomoki Uemura, Janne J. Näppi, Yasuji Ryu, Chinatsu Watari, Tohru Kamiya, Hiroyuki Yoshida

Int. J. Comput. Assist. Radiol. Surg., 2021

Unsupervised survival prediction model from CT images of patients with COVID-19.

Tomoki Uemura, Janne J. Näppi, Chinatsu Watari, Tohru Kamiya, Hiroyuki Yoshida

Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

3D deep learning for computer-aided detection of serrated polyps in CT colonography.

Janne J. Näppi, Tomoki Uemura, Perry J. Pickhardt, David H. Kim, Hiroyuki Yoshida

Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

2020

Correction to: Deep-Sea Organisms Tracking Using Dehazing and Deep Learning.

Huimin Lu, Tomoki Uemura, Dong Wang, Jihua Zhu, Zi Huang, Hyoungseop Kim

Mob. Networks Appl., 2020

Deep-Sea Organisms Tracking Using Dehazing and Deep Learning.

Huimin Lu, Tomoki Uemura, Dong Wang, Jihua Zhu, Zi Huang, Hyoungseop Kim

Mob. Networks Appl., 2020

U-radiomics for predicting survival of patients with idiopathic pulmonary fibrosis.

Tomoki Uemura, Chinatsu Watari, Janne J. Näppi, Toru Hironaka, Hyoungseop Kim, Hiroyuki Yoshida

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Comparative performance of 3D-DenseNet, 3D-ResNet, and 3D-VGG models in polyp detection for CT colonography.

Tomoki Uemura, Janne J. Näppi, Toru Hironaka, Hyoungseop Kim, Hiroyuki Yoshida

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Generative synthetic adversarial network for internal bias correction and handling class imbalance problem in medical image diagnosis.

Mina Rezaei, Tomoki Uemura, Janne Näppi, Hiroyuki Yoshida, Christoph Lippert, Christoph Meinel

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Comparative performance of 3D machine-learning and deep-learning models in the detection of small polyps in dual-energy CT colonography.

Janne J. Näppi, Tomoki Uemura, Se Hyung Kim, Hyoungseop Kim, Hiroyuki Yoshida

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

A Key Recovery Algorithm Using Random Key Leakage from AES Key Schedule.

Tomoki Uemura, Yohei Watanabe, Yang Li, Noriyuki Miura, Mitsugu Iwamoto, Kazuo Sakiyama, Kazuo Ohta

Proceedings of the International Symposium on Information Theory and Its Applications, 2020

2019

Ensemble 3D residual network (E3D-ResNet) for reduction of false-positive polyp detections in CT colonography.

Tomoki Uemura, Janne J. Näppi, Huimin Lu, Hyoungseop Kim, Rie Tachibana, Toru Hironaka, Hiroyuki Yoshida

Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

2018

FDCNet: filtering deep convolutional network for marine organism classification.

Huimin Lu, Yujie Li, Tomoki Uemura, Zongyuan Ge, Xing Xu, Li He, Seiichi Serikawa, Hyoungseop Kim

Multim. Tools Appl., 2018

Low illumination underwater light field images reconstruction using deep convolutional neural networks.

Huimin Lu, Yujie Li, Tomoki Uemura, Hyoungseop Kim, Seiichi Serikawa

Future Gener. Comput. Syst., 2018

2017

Depth Map Reconstruction for Underwater Kinect Camera Using Inpainting and Local Image Mode Filtering.

Huimin Lu, Yin Zhang, Yujie Li, Quan Zhou, Ryunosuke Tadoh, Tomoki Uemura, Hyoungseop Kim, Seiichi Serikawa

IEEE Access, 2017