Medical images provide functional and structural clinical information. Its crucial and urgent to find solutions on enhancing quality of medical images and extracting disease-related information. This report tries to take breast cancer as an example to illustrate basic theories and techniques in medical image analysis and Radiomics. Recent studies and progress in high dimensional reconstruction of complicated medical data, feature extraction, feature reduction, and machine learning are also discussed.

This presentation is part of Minisymposium “MS41 - Framelets, Optimization, and Image Processing (3 parts)”
organized by: Xiaosheng Zhuang (City University of Hong Kong) , Lixin Shen (Syracuse University) , Bin Han (University of Alberta) , Yan-Ran Li (Shenzhen Univeristy) .

Authors:

Yao Lu (Sun Yat-sen University)

Keywords:

image analysis, medical statistics, supervised classification