Structured computer-based training in the interpretation of neuroradiological images

• Published in: International journal of medical informatics (Shannon, Ireland) Vol. 60; no. 3; pp. 263 - 280
• Main Authors: Sharples, M, Jeffery, N.P, du Boulay, B, Teather, B.A, Teather, D, du Boulay, G.H
• Format: Journal Article
• Language: English
• Published: Shannon Elsevier Ireland Ltd 01.12.2000; Elsevier
• Subjects: Artificial Intelligence; Biological and medical sciences; Computer aided diagnosis; Computer-Assisted Instruction; Computer-based training; Forecasting; Humans; Image description; Investigative techniques, diagnostic techniques (general aspects); Medical imaging; Medical sciences; Nervous system; Neurology; Neurology - education; Neuroradiography; Personnel training; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Radiology; Radiology - education; Statistical diagnosis; Image description; Medical imaging; Computer-based training; Statistical diagnosis; Human; Radiography; Biomedical data processing; Educational software program; Radiodiagnosis; Efficiency; Image interpretation; Statistical model; Knowledge representation; Nervous system; Computer aid
• ISSN: 1386-5056; 1872-8243
• DOI: 10.1016/S1386-5056(00)00101-5

Computer-based systems may be able to address a recognised need throughout the medical profession for a more structured approach to training. We describe a combined training system for neuroradiology, the MR Tutor that differs from previous approaches to computer-assisted training in radiology in that it provides case-based tuition whereby the system and user communicate in terms of a well-founded Image Description Language. The system implements a novel method of visualisation and interaction with a library of fully described cases utilising statistical models of similarity, typicality and disease categorisation of cases. We describe the rationale, knowledge representation and design of the system, and provide a formative evaluation of its usability and effectiveness.