Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning
Hidetaka Arimura, Chiaki Tokunaga, Yasuo Yamashita, Jumpei Kuwazuru · Advances in bioinformatics and biomedical engineering book series · 2012
This chapter describes the image analysis for brain Computer-Aided Diagnosis (CAD) systems with machine learning techniques, which could assist radiologists in the detection of such brain diseases as asymptomatic unruptured aneurysms, Alzheimer’s Disease (AD), vascular dementia, and Multiple Sclerosis (MS) by magnetic resonance imaging. Image analysis in CAD systems consists of image enhancement, initial detection, and image feature extraction, including segmentation. In addition, the authors review the classification of true and false positives using machine learning techniques, as well as the evaluation methods and development cycle for CAD systems.