SIFT based ROI extraction for lumbar disk herniation CAD system from MRI axial scans
| Autor: | Brij B. Gupta, Mahmoud Al-Ayyoub, Nusaiba Al-Mnayyis, Mohammad A. Alsmirat, Yaser Jararweh, Khaled Alawneh |
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| Rok vydání: | 2018 |
| Předmět: |
General Computer Science
Matching (graph theory) business.industry Heuristic (computer science) Computer science 0206 medical engineering Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-invariant feature transform 02 engineering and technology 020601 biomedical engineering Lumbar Computer-aided diagnosis Region of interest 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence Focus (optics) business |
| Zdroj: | Journal of Ambient Intelligence and Humanized Computing. |
| ISSN: | 1868-5145 1868-5137 |
| Popis: | 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: | OpenAIRE |
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