| Date: |
2016 |
| 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. |
| Rights: |
Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.  |
| Language: |
Anglès |
| Document: |
Altres ; recerca ; Versió publicada |
| Subject: |
X-ray image ;
Segmentation ;
Entropy ;
Digital straight line segment ;
Concavity index ;
Runs-test ;
Support vector machine |
| Published in: |
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 15 Núm. 2 (2016) , p. 7-9 (Special Issue on Recent PhD Thesis Dissemination (2016)) , ISSN 1577-5097 |
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