WEST LAFAYETTE, Ind. -- Engineers at Purdue University have teamed up with medical experts to develop a computerized system designed to aid in disease diagnosis by matching a patient's CT scans with images in a large data base of scans from previous patients.
Because the images in the data base have been selected by highly trained physicians, the system can be used by less-skilled or less-specialized medical personnel as a tool for diagnosing patients, says Carla Brodley, a computer engineer at Purdue who is leading the research. She stresses that the system is not intended to replace the human element in diagnosis, but to improve the accuracy and speed of diagnosis by completing comprehensive image comparisons within seconds.
"This works through the synergy of human interaction and machine learning and computer vision algorithms," says Brodley, an assistant professor in the Purdue School of Electrical and Computer Engineering.
Sophisticated software enables the user to carry out a visual sort of keyword search, a method referred to as content-based image retrieval. The system views a patient's medical scan and then searches for visually similar images in a data base containing hundreds of CT scans that have been selected carefully by medical experts. The pre-selected scans in the data base represent known examples of specific diseases and conditions, and the four scans that best match the patient's image are retrieved.
The work will be detailed in a paper to appear in the July issue of the
journal Computer Vision and Image Understanding, published by Academic Press
Inc. A poster paper about the research will be presented June 25 during the 1999
IEEE Computer Society Conference on Computer Vision and Pattern Recognition --
which is sponsored by the Institute of Electrical and Electronics Engineers -- in
Fort Collins, Colo. A paper on the work also will be presented at 2 p.m. July 21
during the 16th National Conference on Artifici
Contact: Emil Venere