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Automatic diagnosis of lumbar disc herniation with shape and appearance features from mri.
| Content Provider | CiteSeerX |
|---|---|
| Author | Raja S. Alomari, A. Jason J. Corso, A. Vipin Chaudhary, A. Gurmeet Dhillon, B. |
| Abstract | Intervertebral disc herniation is a major reason for lower back pain (LBP), which is the second most common neurological ailment in the United States. Automation of herniated disc diagnosis reduces the large burden on radiologists who have to diagnose hundreds of cases each day using clinical MRI. We present a method for automatic diagnosis of lumbar disc herniation using appearance and shape features. We jointly use the intensity signal for modeling the appearance of herniated disc and the active shape model for modeling the shape of herniated disc. We utilize a Gibbs distribution for classification of discs using appearance and shape features. We use 33 clinical MRI cases of the lumbar area for training and testing both appearance and shape models. We achieve over 91 % accuracy in detection of herniation in a cross-validation experiment with specificity of 91 % and sensitivity of 94%. Keywords: Lumbar Spine, Herniation, Computer Aided Diagnosis, MRI. 1. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Lumbar Disc Herniation Automatic Diagnosis Appearance Feature Shape Feature Gibbs Distribution Intervertebral Disc Herniation Cross-validation Experiment Lumbar Spine Disc Diagnosis Clinical Mri Back Pain Clinical Mri Case Shape Model Active Shape Model Intensity Signal Common Neurological Ailment Lumbar Area Major Reason United State Computer Aided Diagnosis Large Burden |
| Content Type | Text |
