b'Kensaku Mori'

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Featured Co-authors

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research

∙ 08/08/2023

ConDistFL: Conditional Distillation for Federated Learning from Partially Annotated Data

Developing a generalized segmentation model capable of simultaneously de...

0 Pochuan Wang, et al. ∙

research

∙ 03/27/2023

Identifying Suspicious Regions of Covid-19 by Abnormality-Sensitive Activation Mapping

This paper presents a fully-automated method for the identification of s...

0 Ryo Toda, et al. ∙

research

∙ 02/02/2023

KST-Mixer: Kinematic Spatio-Temporal Data Mixer For Colon Shape Estimation

We propose a spatio-temporal mixing kinematic data estimation method to ...

0 Masahiro Oda, et al. ∙

research

∙ 06/09/2022

Spatial-temporal Concept based Explanation of 3D ConvNets

Recent studies have achieved outstanding success in explaining 2D image ...

0 Ying Ji, et al. ∙

research

∙ 01/14/2022

Semi-automated Virtual Unfolded View Generation Method of Stomach from CT Volumes

CT image-based diagnosis of the stomach is developed as a new way of dia...

6 Masahiro Oda, et al. ∙

research

∙ 01/13/2022

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

This paper proposes a realistic image generation method for visualizatio...

9 Masahiro Oda, et al. ∙

research

∙ 01/12/2022

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

We propose a depth estimation method from a single-shot monocular endosc...

16 Masahiro Oda, et al. ∙

research

∙ 01/09/2022

COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty

This paper proposes a segmentation method of infection regions in the lu...

17 Masahiro Oda, et al. ∙

research

∙ 01/09/2022

Lung infection and normal region segmentation from CT volumes of COVID-19 cases

This paper proposes an automated segmentation method of infection and no...

10 Masahiro Oda, et al. ∙

research

∙ 08/19/2021

Multi-task Federated Learning for Heterogeneous Pancreas Segmentation

Federated learning (FL) for medical image segmentation becomes more chal...

0 Chen Shen, et al. ∙

research

∙ 10/20/2020

Micro CT Image-Assisted Cross Modality Super-Resolution of Clinical CT Images Utilizing Synthesized Training Dataset

This paper proposes a novel, unsupervised super-resolution (SR) approach...

0 Tong Zheng, et al. ∙

research

∙ 09/28/2020

Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning

The performance of deep learning-based methods strongly relies on the nu...

71 Pochuan Wang, et al. ∙

research

∙ 05/07/2020

Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation

This paper proposes a fully automated atlas-based pancreas segmentation ...

6 Masahiro Oda, et al. ∙

research

∙ 05/04/2020

Automated eye disease classification method from anterior eye image using anatomical structure focused image classification technique

This paper presents an automated classification method of infective and ...

0 Masahiro Oda, et al. ∙

research

∙ 04/20/2020

Colonoscope tracking method based on shape estimation network

This paper presents a colonoscope tracking method utilizing a colon shap...

9 Masahiro Oda, et al. ∙

research

∙ 04/07/2020

Super-resolution of clinical CT volumes with modified CycleGAN using micro CT volumes

This paper presents a super-resolution (SR) method with unpaired trainin...

0 Tong Zheng, et al. ∙

research

∙ 03/24/2020

Organ Segmentation From Full-size CT Images Using Memory-Efficient FCN

In this work, we present a memory-efficient fully convolutional network ...

0 Chenglong Wang, et al. ∙

research

∙ 03/03/2020

Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images

This paper presents a visualization method of intestine (the small and l...

0 Hirohisa Oda, et al. ∙

research

∙ 12/30/2019

Multi-modality super-resolution loss for GAN-based super-resolution of clinical CT images using micro CT image database

This paper newly introduces multi-modality loss function for GAN-based s...

61 Tong Zheng, et al. ∙

research

∙ 09/24/2019

Intelligent image synthesis to attack a segmentation CNN using adversarial learning

Deep learning approaches based on convolutional neural networks (CNNs) h...

15 Liang Chen, et al. ∙

research

∙ 08/05/2019

Precise Estimation of Renal Vascular Dominant Regions Using Spatially Aware Fully Convolutional Networks, Tensor-Cut and Voronoi Diagrams

This paper presents a new approach for precisely estimating the renal va...

3 Chenglong Wang, et al. ∙

research

∙ 06/08/2018

3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation

This paper presents a fully automated atlas-based pancreas segmentation ...

8 Masahiro Oda, et al. ∙

research

∙ 06/08/2018

Machine learning-based colon deformation estimation method for colonoscope tracking

This paper presents a colon deformation estimation method, which can be ...

0 Masahiro Oda, et al. ∙

research

∙ 06/06/2018

A multi-scale pyramid of 3D fully convolutional networks for abdominal multi-organ segmentation

Recent advances in deep learning, like 3D fully convolutional networks (...

0 Holger R. Roth, et al. ∙

research

∙ 04/11/2018

Attention U-Net: Learning Where to Look for the Pancreas

We propose a novel attention gate (AG) model for medical imaging that au...

0 Ozan Oktay, et al. ∙

research

∙ 04/11/2018

Unsupervised Segmentation of 3D Medical Images Based on Clustering and Deep Representation Learning

This paper presents a novel unsupervised segmentation method for 3D medi...

0 Takayasu Moriya, et al. ∙

research

∙ 04/11/2018

Unsupervised Pathology Image Segmentation Using Representation Learning with Spherical K-means

This paper presents a novel method for unsupervised segmentation of path...

0 Takayasu Moriya, et al. ∙

research

∙ 03/23/2018

Deep learning and its application to medical image segmentation

One of the most common tasks in medical imaging is semantic segmentation...

0 Holger R. Roth, et al. ∙

research

∙ 03/14/2018

An application of cascaded 3D fully convolutional networks for medical image segmentation

Recent advances in 3D fully convolutional networks (FCN) have made it fe...

0 Holger R. Roth, et al. ∙

research

∙ 01/18/2018

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

Deep learning-based methods achieved impressive results for the segmenta...

0 Chen Shen, et al. ∙

research

∙ 11/17/2017

Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks

Pancreas segmentation in computed tomography imaging has been historical...

0 Holger Roth, et al. ∙

research

∙ 10/15/2017

Towards Automatic Abdominal Multi-Organ Segmentation in Dual Energy CT using Cascaded 3D Fully Convolutional Network

Automatic multi-organ segmentation of the dual energy computed tomograph...

0 Shuqing Chen, et al. ∙

research

∙ 03/15/2017

Comparison of the Deep-Learning-Based Automated Segmentation Methods for the Head Sectioned Images of the Virtual Korean Human Project

This paper presents an end-to-end pixelwise fully automated segmentation...

0 Mohammad Eshghi, et al. ∙

research

∙ 02/27/2017

Multi-scale Image Fusion Between Pre-operative Clinical CT and X-ray Microtomography of Lung Pathology

Computational anatomy allows the quantitative analysis of organs in medi...

0 Holger R. Roth, et al. ∙

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