81 citations · 189 across the 18 of their papers we have counts for
6 papers · 1 filter
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…
BMD-GAN: Bone mineral density estimation using x-ray image decomposition into projections of bone-segmented quantitative computed tomography using hierarchical learning
Yi Gu, Yoshito Otake, Keisuke Uemura +4
We propose a method for estimating the bone mineral density (BMD) from a plain x-ray image. Dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT) provid…
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…
Estimation of Pelvic Sagittal Inclination from Anteroposterior Radiograph Using Convolutional Neural Networks: Proof-of-Concept Study
Ata Jodeiri, Yoshito Otake, Reza A. Zoroofi +5
Alignment of the bones in standing position provides useful information in surgical planning. In total hip arthroplasty (THA), pelvic sagittal inclination (PSI) angle in the standi…
Automated Muscle Segmentation from Clinical CT using Bayesian U-Net for Personalized Musculoskeletal Modeling
Yuta Hiasa, Yoshito Otake, Masaki Takao +3
We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using M…