Paper Info
Title
Disc Herniation Diagnosis In Mri Using A Cad Framework And A Two-Level Classifier
Abstract
Purpose Disc herniation in the lumbar spine is a common condition, so an automated method for diagnosis could be helpful in clinical applications. A computer-aided framework for disk herniation diagnosis was developed for use in magnetic resonance imaging (MRI).Materials and Method A computer-aided diagnosis framework for lumbar spine with a two-level classification scheme for disc herniation diagnosis was developed using heterogeneous classifiers: a perceptron classifier, a least mean square classifier, a support vector machine classifier, and a k-Means classifier. Each classifier makes a diagnosis based on a feature set generated from regions of interest that contain vertebrae, a disc, and the spinal cord. Then, an ensemble classifier makes a final decision using score values of each classifier. We used clinical MR image data from 70 subjects in T1-weighted sagittal view and T2-weighted sagittal view for evaluation of the system.Results MR images of 70 subjects were processed using the proposed framework resulting in successful detection of disc herniation with 99% accuracy, achieving a speedup factor of 30 in comparison with radiologist's diagnosis.Conclusion The computer-aided framework works well to diagnose herniated discs in MRI scans. We expect the framework can be adapted to effectively diagnose a variety of abnormalities in the lumbar spine.
Year
DOI
Venue
2012
10.1007/s11548-012-0674-9
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
Keywords
Field
DocType
Lower back pain, Computer-aided diagnosis, Classifier, Disc herniation, Lumbar spine, MRI
CAD,Computer-aided diagnosis,Lumbar,Radiology,Classifier (linguistics),Medicine,Magnetic resonance imaging
Journal
Volume
Issue
ISSN
7
6
1861-6410
Citations 
PageRank 
References 
3
0.42
5
Authors
3
Name
Order
Citations
PageRank
Jaehan Koh1565.11
Vipin Chaudhary283883.24
Gurmeet Dhillon313011.09