E. Alberdi, P. Taylor, R. Lee
CHIME, University College London, UK
Knowledge Representation, Image processing, Computer aided diagnosis, radiology, knowledge elicitation
Objectives: To study how professional radiologists describe, interpret and make decisions about microcalcifications in mammograms. The purpose was to develop a model of the radiologists’ decision making for use in CADMIUM II, a computerized aid for mammogram interpretation that combines symbolic reasoning with image processing. Methods: In Study 1, eleven radiologists were asked to ‘think out loud’ as they interpreted 20 sets of calcifications. Participants used 159 terms to describe calcifications. We used these data to design a scheme with 50 descriptors. In Study 2, ten radiologists used the scheme to describe 40 sets of calcifications. We assessed the capacity of the terms to discriminate between benign and malignant calcifications, testing them against radiologists’ assessments of malignancy and follow-up data. Results: The descriptors that were found to be the most discriminating in Study 2 were included in CADIMUM II’s knowledge base. They were represented as arguments for either a benign or a malignant diagnosis. These arguments are the central component of the decision support provided by the system. Other components are: image processing algorithms for the detection and measurement of calcifications and a set of rules that use the measures to decide which of the arguments apply to a given set of calcifications. Conclusions: Preliminary evaluations of the CADMIUM II prototype reinforce the value of representing explicitly decision making processes in computer aided mammography and of deriving these processes from image processing measurements. Decision support is presented here at a level of description that is both relevant and meaningful to the user.
A.-M. Rassinoux, Managing Editor for the IMIA Yearbook Section on Decision Support, Knowledge Representation and Management1
IMIA Yearbook 2008 3: 80-82
R. Grütter (1) , W. Fierz (2)
Methods Inf Med 1999 38 3: 154-157
B. Brigl, Managing Editor for the IMIA Yearbook Section on Decision Support, Knowledge Representation and Management
IMIA Yearbook 2007 2: 87-88
Information technology in health care has a clear potential to improve the quality and efficiency...
The submission deadline for the Focus Theme on "Big Data and Analytics in Healthcare"...
Medical informatics, biometry and epidemiology are closely related disciplines that contribute...