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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

Hidetaka Arimura, Chiaki Tokunaga, Yasuo Yamashita, Jumpei Kuwazuru
Copyright: © 2012 |Pages: 39
ISBN13: 9781466600591|ISBN10: 1466600594|EISBN13: 9781466600607
DOI: 10.4018/978-1-4666-0059-1.ch013
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MLA

Arimura, Hidetaka, et al. "Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning." Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis, edited by Kenji Suzuki, IGI Global, 2012, pp. 258-296. https://doi.org/10.4018/978-1-4666-0059-1.ch013

APA

Arimura, H., Tokunaga, C., Yamashita, Y., & Kuwazuru, J. (2012). Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning. In K. Suzuki (Ed.), Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis (pp. 258-296). IGI Global. https://doi.org/10.4018/978-1-4666-0059-1.ch013

Chicago

Arimura, Hidetaka, et al. "Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning." In Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis, edited by Kenji Suzuki, 258-296. Hershey, PA: IGI Global, 2012. https://doi.org/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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