7 citations · 10 across the 6 of their papers we have counts for
6 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,…
Deep Learning Estimation of Sex, Age, Height, and Weight from CT-derived Digitally Reconstructed Radiographs
Tomohiro Kikuchi, Kohei Yamamoto, Yukihiro Nomura +6
Purpose: To develop and validate a deep learning ensemble for estimating adult sex, age, height, and weight from coronal digitally reconstructed radiographs (DRRs) generated from d…
Identifying Suspicious Regions of Covid-19 by Abnormality-Sensitive Activation Mapping
Ryo Toda, Hayato Itoh, Masahiro Oda +6
This paper presents a fully-automated method for the identification of suspicious regions of a coronavirus disease (COVID-19) on chest CT volumes. One major role of chest CT scanni…
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…
Lung infection and normal region segmentation from CT volumes of COVID-19 cases
Masahiro Oda, Yuichiro Hayashi, Yoshito Otake +3
This paper proposes an automated segmentation method of infection and normal regions in the lung from CT volumes of COVID-19 patients. From December 2019, novel coronavirus disease…