2 citations · 6 across the 9 of their papers we have counts for
9 papers
Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer
Masahiro Oda, Tong Zheng, Yuichiro Hayashi +5
This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID-19) spreads over the world, c…
Automated classification method of COVID-19 cases from chest CT volumes using 2D and 3D hybrid CNN for anisotropic volumes
Masahiro Oda, Tong Zheng, Yuichiro Hayashi +5
This paper proposes an automated classification method of chest CT volumes based on likelihood of COVID-19 cases. Novel coronavirus disease 2019 (COVID-19) spreads over the world,…
Exploiting Memory-aware Q-distribution Prediction for Nuclear Fusion via Modern Hopfield Network
Qingchuan Ma, Shiao Wang, Tong Zheng +4
This study addresses the critical challenge of predicting the Q-distribution in long-term stable nuclear fusion task, a key component for advancing clean energy solutions. We intro…
TNF: Tri-branch Neural Fusion for Multimodal Medical Data Classification
Tong Zheng, Shusaku Sone, Yoshitaka Ushiku +2
This paper presents a Tri-branch Neural Fusion (TNF) approach designed for classifying multimodal medical images and tabular data. It also introduces two solutions to address the c…
COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty
Masahiro Oda, Tong Zheng, Yuichiro Hayashi +5
This paper proposes a segmentation method of infection regions in the lung from CT volumes of COVID-19 patients. COVID-19 spread worldwide, causing many infected patients and death…
Micro CT Image-Assisted Cross Modality Super-Resolution of Clinical CT Images Utilizing Synthesized Training Dataset
Tong Zheng, Hirohisa Oda, Masahiro Oda +5
This paper proposes a novel, unsupervised super-resolution (SR) approach for performing the SR of a clinical CT into the resolution level of a micro CT (CT). The precise non-inv…
Super-resolution of clinical CT volumes with modified CycleGAN using micro CT volumes
Tong ZHENG, Hirohisa ODA, Takayasu MORIYA +7
This paper presents a super-resolution (SR) method with unpaired training dataset of clinical CT and micro CT volumes. For obtaining very detailed information such as cancer invasi…
Multi-modality super-resolution loss for GAN-based super-resolution of clinical CT images using micro CT image database
Tong Zheng, Hirohisa Oda, Takayasu Moriya +6
This paper newly introduces multi-modality loss function for GAN-based super-resolution that can maintain image structure and intensity on unpaired training dataset of clinical CT…
DeepIlluminance: Contextual Illuminance Estimation via Deep Neural Networks
Jun Zhang, Tong Zheng, Shengping Zhang +1
Computational color constancy refers to the estimation of the scene illumination and makes the perceived color relatively stable under varying illumination. In the past few years,…