17 citations · 34 across the 3 of their papers we have counts for
5 papers
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…
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…
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…