Author:
Verghese Jenny Ann,Pamela D.,Michael Prawin Angel,Meenal R.
Abstract
Abstract
Rheumatoid Arthritis (RA) may be a general disease characterized by inflammation, discomfort, and tenderness of the joints and might involve additional body part organs in severe cases. Leading to increased vascular disorder in the zone of inflammatory tissue, joint autoimmune lesions are associated with elevated fever. The detection of RA usually involves blood sample tests. This thesis proposes a novel methodology of detection by processing the Xray images. This automated system requires clear Xray images, which after preprocessing and segmentation using Support Vector Machine implemented via MATLAB gives a clear classification about the abnormal and normal images. Different output parameters were used to assess separation tasks. The accuracy of the model section has improved to the use of an optimized SVM network. The proposed model was effective in accurately separating the samples.
Subject
General Physics and Astronomy
Reference18 articles.
1. Skeletal bone age assessment–research directions;Thangam;Journal of Engineering Science and Technology Review,2012
2. On edge detection of x-ray images using fuzzy sets;Pal;Pattern Analysis and Machine Intelligence, IEEE Transactions,1983
3. An automatic system for skeletal bone age measurement by robust processing of carpal and epiphysial/metaphysial bones;Giordano;Instrumentation and Measurement, IEEE Transactions on,2010
4. Computer-assisted bone age assessment: Image preprocessing and epiphyseal/metaphyseal roi extraction;Pietka;Medical Imaging, IEEE Transactions on,2001
5. Are the new automated methods for bone age estimation advantageous over the manual approaches?;Vincenzo De Sanctis;Pediatric Endocrinology Reviews (PER),2014
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