Detection of Disc Destruction Between Lumbar Vertebrae Using MRI Images

Document Type : Original Article

Authors

1 Faculty of Electrical and Computer Engineering, Pars Razavi University, Gonabad, Iran

2 Faculty of Electrical and Computer Engineering, Gonabad Higher Education Complex, Gonabad, Iran

Abstract

Most people experience low back pain at least once in their lifetime. Lumbar disc herniation is one of the major causes of low back pain. Treatment methods for disc herniation are very diverse. Therefore, diagnosis of the exact size of herniation and its location can greatly help specialists to select the best treatment method. In this research, an automated method for diagnosing lumbar disc herniation using 130 MR images is proposed. In the proposed method, using three algorithms, namely region growing, OTSU and active contour, the intervertebral discs and their boundary were precisely separated from the background of the image. In the next step, after extracting the most significant features of the images, they are divided into healthy and unhealthy classes by SVM classifier with 89.9% accuracy. The classification accuracy was compared with classifiers KNN, Ensemble, and decision tree. Finally, it was determined the SVM classifier has the highest accuracy for the classification.

Keywords

References

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History

  • Receive Date: 01 October 2020
  • Revise Date: 21 April 2021
  • Accept Date: 10 May 2021

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