An artificial intelligence program for the radiologic diagnosis of brain lesions.
A software program has been developed that uses a frame-based expert system for differential diagnosis in neuroradiology. A frame-based expert system is used to store the magnetic resonance (MR) and computed tomographic (CT) imaging characteristics of over 100 known brain disorders in object-like entities. The frames are organized in a hierarchic structure in which lower order frames inherit attributes from higher order frames, with the highest frame containing information that applies to all the other frames. Program execution follows a consultation paradigm with a dynamic database. A decision tree menu provides a user-friendly interface with which to navigate through the network, based on features of the lesion as depicted on MR and CT images. The system can provide a differential diagnosis based on the MR imaging findings alone with information criteria including the signal intensity of the lesion on T1- and T2-weighted images, the location of the lesion, and the presence or absence of mass effect. The differential diagnosis may be further refined by adding CT-related information, including CT attenuation and the presence or absence of calcification and contrast enhancement.
Department of Radiology, Ottawa General Hospital, University of Ottawa, Ontario, Canada.
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P
Rasuli
F
F
Rasouli
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DI
Hammond
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F
Amiri
D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D005103:Expert Systems; D006801:Humans; D008279:Magnetic Resonance Imaging; D014057:Tomography, X-Ray Computed