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Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning

Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning
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Author(s): Hidetaka Arimura (Kyushu University, Japan), Chiaki Tokunaga (Kyushu University, Japan), Yasuo Yamashita (Kyushu University, Japan)and Jumpei Kuwazuru (Kyushu University, Japan)
Copyright: 2012
Pages: 39
Source title: Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis
Source Author(s)/Editor(s): Kenji Suzuki (University of Chicago, USA)
DOI: 10.4018/978-1-4666-0059-1.ch013

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Abstract

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.

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