Transactions on Machine Learning and Data Mining (ISSN: 1865-6781)
Volume 11 - Number 1 - July 2018 - Pages 3-25
Mining Knowledge for Differential Diagnosis of Pulmonary Nodules
P. Perner, T.P. Belikova¹, I. Stenina¹
Institute of Computer Vision and Applied Computer Sciences IBaI, Germany,
¹Institute for Information Transmission Problems Russian Academy of Sciences, Moscow, Russia
Abstract
Development of computer-assisted radiology in PACS is associated with the use of new intelligent capabilities of Computer-Assisted Radiology. In this paper we present our work on data mining to support medical image diagnosis. We use decision tree induction in order to learn the expert knowledge, presented in the form of image descriptions in the database. A methodology is developed to perform data mining in picture archiving systems. The tool for data mining is presented. It was applied in the task of early differential diagnosis of pulmonary nodules in lung tomograms and allowed to support image analysis and classification by the expert. Results of knowledge acquisition on the basis of data mining are presented and compared with the results of the semi-automatic method of knowledge acquisition by a Syndrome framework tool. The developed decision tree and developed Syndrome-like decision rule were effective for early diagnosis of peripheral lung cancer, so that we are able to apply this method to other medical tasks, in particular, for image analysis in mammography.
Keywords:Data Mining, Decision Support, Image Interpretation, Decision Trees, Syndrome Classifier
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