Abstract
This thesis reports several methods for automated analysis and interpretation of bone X-ray images. Automatic segmentation of the bone part in a digital X-ray image is a challenging problem because of its low contrast against the surrounding flesh. In this thesis, we propose a fully automated X-ray image segmentation technique, which is based on a variant of entropy measure of the image. We have also analyzed the geometric information embedded in the long-bone contour image to identify the presence of abnormalities in the bone and perform fracture detection, fracture classification, and bone cancer diagnosis.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: ELCVIA Electronic Letters on Computer Vision and Image Analysis
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
