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Statistical and Adaptive Approaches for Optimal Segmentation in Medical Images

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Handbook of Biomedical Image Analysis

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Abstract

Image analysis techniques have been broadly used in computer-aided medical analysis and diagnosis in recent years. Computer-aided image analysis is an increasingly popular tool in medical research and practice, especially with the increase of medical images in modality, amount, size, and dimension. Image segmentation, a process that aims at identifying and separating regions of interests from an image, is crucial in many medical applications such as localizing pathological regions, providing objective quantative assessment and monitoring of the onset and progression of the diseases,as well as analysis of anatomical structures.

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  1. Department of Electrical and Computer Engineering, Texas Tech University Lubbock, TX, 79409-3102

    Shuyu Yang & Sunanda Mitra

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  1. Shuyu Yang
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  2. Sunanda Mitra
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  1. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio

    Jasjit S. Suri  & David L. Wilson  & 

  2. Institute of Rural Health, Idaho State University, Pocatello, Idaho

    Swamy Laxminarayan

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Yang, S., Mitra, S. (2005). Statistical and Adaptive Approaches for Optimal Segmentation in Medical Images. In: Suri, J.S., Wilson, D.L., Laxminarayan, S. (eds) Handbook of Biomedical Image Analysis. Topics in Biomedical Engineering International Book Series. Springer, Boston, MA. https://doi.org/10.1007/0-306-48606-7_6

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