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20172022
most citedOn the influence of Dice loss function in multi-class organ segmentation of abdominal CT using 3D fully convolutional networks

31 citations · 157 across the 20 of their papers we have counts for

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12 papers · 1 filter

eess.IV2022

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…

eess.IV202217 cited

Realistic Endoscopic Image Generation Method Using Virtual-to-real Image-domain Translation

Masahiro Oda, Kiyohito Tanaka, Hirotsugu Takabatake +3

This paper proposes a realistic image generation method for visualization in endoscopic simulation systems. Endoscopic diagnosis and treatment are performed in many hospitals. To r…

eess.IV202216 cited

Depth Estimation from Single-shot Monocular Endoscope Image Using Image Domain Adaptation And Edge-Aware Depth Estimation

Masahiro Oda, Hayato Itoh, Kiyohito Tanaka +4

We propose a depth estimation method from a single-shot monocular endoscopic image using Lambertian surface translation by domain adaptation and depth estimation using multi-scale…

eess.IV20222 cited

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…

eess.IV20227 cited

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…

eess.IV2020

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…