31 citations · 41 across the 7 of their papers we have counts for
5 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…
Semi-automated Virtual Unfolded View Generation Method of Stomach from CT Volumes
Masahiro Oda, Tomoaki Suito, Yuichiro Hayashi +9
CT image-based diagnosis of the stomach is developed as a new way of diagnostic method. A virtual unfolded (VU) view is suitable for displaying its wall. In this paper, we propose…
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…
Precise Estimation of Renal Vascular Dominant Regions Using Spatially Aware Fully Convolutional Networks, Tensor-Cut and Voronoi Diagrams
Chenglong Wang, Holger R. Roth, Takayuki Kitasaka +7
This paper presents a new approach for precisely estimating the renal vascular dominant region using a Voronoi diagram. To provide computer-assisted diagnostics for the pre-surgica…