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Image Analysis Techniques for the Quantification of Brain Tumors on MR Images

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Computational Intelligence in Biomedical Imaging

Abstract

Advances in neuro-imaging methods over the last few decades have enabled collection of detailed anatomical and functional information about the brain. Although functional imaging provides rich information for diagnosis and treatment planning, practical considerations such as cost and availability currently limit its clinical utility. As a result, structural imaging methods that provide detailed information about the anatomical structures of the brain are routinely used to manage brain tumors in the clinical setting. Typically, radiological images are visually inspected and interpreted by trained health professionals to detect gross anatomical abnormalities, which are associated with various types of brain tumors. This approach entails generally qualitative interpretations that do not fully realize the potential of modern imaging technologies. Furthermore, several types of brain tumors manifest with gross anatomical changes that are visually similar, which limits the use of MRI in differentiating between them. Computer-aided image analysis enables a quantitative description of brain anatomy and detection of subtle, but important, anatomical changes that may be difficult to detect by visual inspection. Therefore, it’s imperative to develop sophisticated image analysis tools that can handle the highly complex and varied organization of the brain across individuals. Such tools will form the foundation for decision support systems (DSSs) to aid health professionals in more precise and personalized management of brain tumors.

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Authors and Affiliations

  1. Department of Biomedical Engineering, The University of Texas at Austin, 107 W Dean Keeton Street Stop, 1 University Station, C0800, Austin, TX, 78712, USA

    Nishant Verma & Mia K. Markey

  2. NeuroTexas Institute, St. David’s HealthCare, 1015 East 32nd Street Suite 404, Austin, TX, 78705, USA

    Nishant Verma, Matthew C. Cowperthwaite & Mark G. Burnett

  3. Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA

    Mia K. Markey

Authors
  1. Nishant Verma
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  2. Matthew C. Cowperthwaite
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  3. Mark G. Burnett
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  4. Mia K. Markey
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Correspondence to Nishant Verma .

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Editors and Affiliations

  1. Department of Radiology, University of Chicago, Chicago, Illinois, USA

    Kenji Suzuki

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Verma, N., Cowperthwaite, M.C., Burnett, M.G., Markey, M.K. (2014). Image Analysis Techniques for the Quantification of Brain Tumors on MR Images. In: Suzuki, K. (eds) Computational Intelligence in Biomedical Imaging. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7245-2_11

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  • DOI: https://doi.org/10.1007/978-1-4614-7245-2_11

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