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Image Enhancement and Segmentation Techniques for Detection of Knee Joint Diseases: A Survey

期刊

CURRENT MEDICAL IMAGING REVIEWS
卷 14, 期 5, 页码 704-715

出版社

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/1573405613666170912164546

关键词

Knee bone disease; knee image analysis; MRI; knee image segmentation; features mining; knee cancers

资金

  1. Machine Learning Research Group
  2. Prince Sultan University Riyadh
  3. Saudi Arabia [RG-CCIS-2017-06-02]

向作者/读者索取更多资源

Background: Knee bone diseases are rare but might be highly destructive. Magnetic Resonance Imaging (MRI) is the main approach to identify knee cancer and its treatment. Normally, the knee cancers are detected with the help of different MRI analysis techniques and later image analysis strategies assess these images. Discussion: Computer-based medical image analysis is getting researcher's interest due to its advantages of speed and accuracy as compared to traditional techniques. The focus of current research is MRI-based medical image analysis for knee bone disease detection. Accordingly, several approaches for features extraction and segmentation for knee bone cancer are analyzed and compared on benchmark database. Conclusion: Finally, the current state of the art is investigated and future directions are proposed.

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