Segmentation of Lumbar Spine MRI Images for Stenosis Detection Using Patch-Based Pixel Classification Neural Network

Ala S. Al Kafri, Sud Sudirman, Abir J. Hussain, Dhiya Al-Jumeily, Paul Fergus, Friska Natalia, Hira Meidia, Nunik Afriliana, Ali Sophian, Mohammed Al-Jumaily, Wasfi Al-Rashdan, Mohammad Bashtawi

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper addresses the central problem of automatic segmentation of lumbar spine Magnetic Resonance Imaging (MRI) images to delineate boundaries between the anterior arch and posterior arch of the lumbar spine. This is necessary to efficiently detect the occurrence of lumbar spinal stenosis as a leading cause of Chronic Lower Back Pain. A patch-based classification neural network consisting of convolutional and fully connected layers is used to classify and label pixels in MRI images. The classifier is trained using overlapping patches of size 25×25 pixels taken from a set of cropped axial-view T2-weighted MRI images of the bottom three intervertebral discs. A set of experiment is conducted to measure the performance of the classification network in segmenting the images when either all or each of the discs separately is used. Using pixel accuracy, mean accuracy, mean Intersection over Union (IoU), and frequency weighted IoU as the performance metrics we have shown that our approach produces better segmentation results than eleven other pixel classifiers. Furthermore, our experiment result also indicates that our approach produces more accurate delineation of all important boundaries and making it best suited for the subsequent stage of lumbar spinal stenosis detection.
    Original languageEnglish
    Title of host publication2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Print)9781509060177
    DOIs
    Publication statusPublished - 28 Sep 2018
    Event2018 IEEE Congress on Evolutionary Computation - Rio de Janeiro, Brazil
    Duration: 8 Jul 201813 Jul 2018

    Publication series

    Name2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings

    Conference

    Conference2018 IEEE Congress on Evolutionary Computation
    CountryBrazil
    CityRio de Janeiro
    Period8/07/1813/07/18

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  • Cite this

    Al Kafri, A. S., Sudirman, S., Hussain, A. J., Al-Jumeily, D., Fergus, P., Natalia, F., Meidia, H., Afriliana, N., Sophian, A., Al-Jumaily, M., Al-Rashdan, W., & Bashtawi, M. (2018). Segmentation of Lumbar Spine MRI Images for Stenosis Detection Using Patch-Based Pixel Classification Neural Network. In 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2018.8477893