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Toward a computer aided diagnosis system for lumbar disc herniation disease based on MR images analysis

Nikravan, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.4015/S1016237216500423
  3. Publisher: World Scientific Publishing Co. Pte Ltd
  4. Abstract:
  5. Lumbar disc diseases are the commonest complaint of Lower Back Pain (LBP). In this paper, a new method for automatic diagnosis of lumbar disc herniation is proposed which is based on clinical Magnetic Resonance Images (MRI) data. We use T2-W sagittal and myelograph images. Our method uses Otsu thresholding method to extract the spinal cord from MR images of Lumbar disc. In the next step, a third-order polynomial is aligned on the extracted spinal cords, and in the end of preprocessing step all the T2-W sagittal images are prepared for extracting disc boundary and labeling. After labeling and extracting a ROI for each disc, intensity and shape features are used for classification. The presented Method is applied on 30 clinical cases, each containing 7 discs (210 lumbar discs) for the herniation diagnosis. The results revealed 92.38% and 93.80% accuracy for Artificial Neural Network and Support Vector Machine (SVM) classifiers, respectively. The results indicate the superiority of the proposed method to those mentioned in similar studies
  6. Keywords:
  7. LBP ; Lumbar disc diseases ; MRI ; Computer aided analysis ; Diagnosis ; Image processing ; Laser tissue interaction ; Magnetic resonance ; Magnetic resonance imaging ; Neural networks ; Support vector machines ; Automatic diagnosis ; Herniation ; Lumbar disc ; Myelograph ; Spinal cords ; Computer aided diagnosis
  8. Source: Biomedical Engineering - Applications, Basis and Communications ; Volume 28, Issue 6 , 2016 ; 10162372 (ISSN)
  9. URL: http://www.worldscientific.com/doi/abs/10.4015/S1016237216500423