57 citations · 64 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…
Fusing Medical Image Features and Clinical Features with Deep Learning for Computer-Aided Diagnosis
Songxiao Yang, Xiabi Liu, Zhongshu Zheng +2
Current Computer-Aided Diagnosis (CAD) methods mainly depend on medical images. The clinical information, which usually needs to be considered in practical clinical diagnosis, has…
A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms
Said Boumaraf, Xiabi Liu, Chokri Ferkous +1
Mammography remains the most prevalent imaging tool for early breast cancer screening. The language used to describe abnormalities in mammographic reports is based on the breast Im…
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…