| Autor: |
Al-Ayyoub, Mahmoud, Al-Mnayyis, Nusaiba, Alsmirat, Mohammad, Alawneh, Khaled, Jararweh, Yaser, Gupta, Brij |
| Zdroj: |
Journal of Ambient Intelligence and Humanized Computing; 20240101, Issue: Preprints p1-9, 9p |
| Abstrakt: |
Computer-aided diagnosis (CAD) systems have been the focus of many research endeavors. We consider the problem of building a CAD system for diagnosing lumbar disk herniation from MRI axial scans. Like other typical image based CAD systems, the CAD system we consider consists of several stages: image acquisition, region of interest (ROI) extraction and enhancement, feature extraction, and classification. Experimentally, we found that the ROI extraction is the hardest stage and it greatly determines the accuracy of the CAD system. In this work, we enhance on the ROI extraction process by using SIFT features, which are well known for their use in matching objects. The experiments conducted to evaluate the SIFT based ROI extraction approach shows its superiority over existing heuristic approach. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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