Availability of digital data within picture archiving and communication systems raises a possibility of health care and research enhancement associated with manipulation, processing and handling of data by computers. That is the basis for computer-assisted radiology development. Further development of computer-assisted radiology is associated with the use of new intelligent capabilities such as multimedia support and data mining in order to discover the relevant knowledge for diagnosis. In this paper, we present our work on data mining in medical picture archiving systems. We use decision tree induction in order to learn the knowledge for computer- assisted image analysis. We are applying our method to interpretation of x-ray images for lung cancer diagnosis. We are describing our methodology on how to perform data mining on picture archiving systems and our tool for data mining. Results are given. The method has shown very good results so that we are going on to apply it to other medical image diagnosis tasks such as lymph node diagnosis in MRI and investigation of breast MRI.
Petra Perner, Petra Perner,
"Mining knowledge in medical image databases", Proc. SPIE 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, (6 April 2000); doi: 10.1117/12.381752; https://doi.org/10.1117/12.381752