5 citations · 9 across the 4 of their papers we have counts for
4 papers
Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation
Huiyu Li, Xiabi Liu, Said Boumaraf +3
Small object segmentation, like tumor segmentation, is a difficult and critical task in the field of medical image analysis. Although deep learning based methods have achieved prom…
RL-CoSeg : A Novel Image Co-Segmentation Algorithm with Deep Reinforcement Learning
Xin Duan, Xiabi Liu, Xiaopeng Gong +1
This paper proposes an automatic image co-segmentation algorithm based on deep reinforcement learning (RL). Existing co-segmentation tasks mainly rely on deep learning methods, and…
A Dense Siamese U-Net trained with Edge Enhanced 3D IOU Loss for Image Co-segmentation
Xi Liu, Xiabi Liu, Huiyu Li +1
Image co-segmentation has attracted a lot of attentions in computer vision community. In this paper, we propose a new approach to image co-segmentation through introducing the dens…
A New Three-stage Curriculum Learning Approach to Deep Network Based Liver Tumor Segmentation
Huiyu Li, Xiabi Liu, Said Boumaraf +3
Automatic segmentation of liver tumors in medical images is crucial for the computer-aided diagnosis and therapy. It is a challenging task, since the tumors are notoriously small a…