TOWARD A COMPUTER AIDED DIAGNOSIS SYSTEM FOR LUMBAR DISC HERNIATION DISEASE BASED ON MR IMAGES ANALYSIS
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.