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Detection of Focal Cortical Dysplasia lesions in MR images

Published: 09 April 2020 Publication History

Abstract

Focal cortical dysplasia (FCD) is the most common factor leading to intractable epilepsy. It is helpful for doctors to automatically detect the FCD lesion before the operation. In this study, two methods to detect and locate the lesion are proposed. The first method is based on the symmetrical characteristics of the brain image, and can approximately detect abnormal areas caused by FCD in Magnetic Resonance (MR) images. The second method involves detecting local highlighted areas in MR images based on the expectation-maximization (EM) algorithm. The two methods were applied to 15 specific MR images of 9 epileptic patients. The recognition accuracy of the symmetrical feature algorithm and EM algorithm was 80 % (12/15) and 100% (15/15), respectively, and the detection accuracy of the combination of two algorithms is 80%. The symmetrical feature algorithm can be applied to any of the axial or coronal MR images of the modality, and the EM algorithm is suitable for detecting the local hyperintense of the MR image. The two methods were able to detect lesion areas in MR images and achieve desirable results.

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  1. Detection of Focal Cortical Dysplasia lesions in MR images

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    BDET '20: Proceedings of the 2020 2nd International Conference on Big Data Engineering and Technology
    January 2020
    126 pages
    ISBN:9781450376839
    DOI:10.1145/3378904
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • Natl University of Singapore: National University of Singapore
    • Southwest Jiaotong University

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 09 April 2020

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    Author Tags

    1. Detection
    2. EM
    3. FCD
    4. MR image
    5. Symmetrical feature

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    • NSAF
    • The National Key R&D Program of China

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