27 citations · 40 across the 4 of their papers we have counts for
8 papers
Efficient and Accurate Hyperspectral Pansharpening Using 3D VolumeNet and 2.5D Texture Transfer
Yinao Li, Yutaro Iwamoto, Ryousuke Nakamura +3
Recently, convolutional neural networks (CNN) have obtained promising results in single-image SR for hyperspectral pansharpening. However, enhancing CNNs' representation ability wi…
Genotype-Guided Radiomics Signatures for Recurrence Prediction of Non-Small-Cell Lung Cancer
Panyanat Aonpong, Yutaro Iwamoto, Xian-Hua Han +2
Non-small cell lung cancer (NSCLC) is a serious disease and has a high recurrence rate after the surgery. Recently, many machine learning methods have been proposed for recurrence…
Graph-based Pyramid Global Context Reasoning with a Saliency-aware Projection for COVID-19 Lung Infections Segmentation
Huimin Huang, Ming Cai, Lanfen Lin +9
Coronavirus Disease 2019 (COVID-19) has rapidly spread in 2020, emerging a mass of studies for lung infection segmentation from CT images. Though many methods have been proposed fo…
PA-ResSeg: A Phase Attention Residual Network for Liver Tumor Segmentation from Multi-phase CT Images
Yingying Xu, Ming Cai, Lanfen Lin +10
In this paper, we propose a phase attention residual network (PA-ResSeg) to model multi-phase features for accurate liver tumor segmentation, in which a phase attention (PA) is new…
VolumeNet: A Lightweight Parallel Network for Super-Resolution of Medical Volumetric Data
Yinhao Li, Yutaro Iwamoto, Lanfen Lin +2
Deep learning-based super-resolution (SR) techniques have generally achieved excellent performance in the computer vision field. Recently, it has been proven that three-dimensional…
Interactive Deep Refinement Network for Medical Image Segmentation
Titinunt Kitrungrotsakul, Iwamoto Yutaro, Lanfen Lin +3
Deep learning techniques have successfully been employed in numerous computer vision tasks including image segmentation. The techniques have also been applied to medical image segm…