Automatic medical X-ray image classification using annotation.

摘要: The demand for automatically classification of medical X-ray images is rising faster than ever. In this paper, an approach presented to gain high accuracy rate those classes database with ratio intraclass variability and interclass similarities. framework was constructed via annotation using the following three techniques: by binary classification, probabilistic latent semantic analysis, top similar images. Next, final applying ranking similarity on annotated keywords made each technique. were then divided into levels according body region, specific bone structure in region as well imaging direction. Different weights given level keywords; they are used calculate weightage category based their ground truth annotation. computed from generated query image compared images, would be assigned closest image. average reported 87.5 %.