Abstract
Computer-aided diagnosis systems have been the focus of many research endeavours. In addition to being a great asset for any hospital, such systems represent invaluable platforms for educational and research purposes. In this work, we propose a system for the diagnosis and training on the diagnosis of lumbar disk herniation from magnetic resonance imaging (MRI) scans. The proposed system has three main novel contributions. First, it utilises the axial MRI spine view of the suspected region instead of using MRI sagittal spine view. Second, instead of simply classifying cases as normal or abnormal, the proposed system is capable of determining the type of lumbar disk herniation and pinpoints its location. The final contribution is the simulated training environment that can be used to train novice radiologists on the diagnosis of lumbar disk herniation. Our experiments show that it is quick and accurate besides being very useful for training purposes.
| Original language | English |
|---|---|
| Pages (from-to) | 295-317 |
| Number of pages | 23 |
| Journal | International Journal of Advanced Intelligence Paradigms |
| Volume | 22 |
| Issue number | 3-4 |
| DOIs | |
| State | Published - 2022 |
| Externally published | Yes |
Keywords
- CAD
- ROI enhancement
- ROI extraction
- axial MRI spine view
- classification
- computer-aided diagnosis
- feature extraction
- lumbar disk herniation
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