期刊名称：ELCVIA: electronic letters on computer vision and image analysis
印刷版ISSN：1577-5097
出版年度：2016
卷号：15
期号：2
页码：7-9
DOI：10.5565/rev/elcvia.970
语种：English
出版社：Centre de Visió per Computador
摘要：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.
其他摘要：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.
关键词：X-ray image, Segmentation, Entropy, Digital Straight line segment, Concavity index, Runs-test, Support vector machine
