Computer Aided Detection as a Decision Aid in Medical Screening

M. Samulski

Promotor: N. Karssemeijer and P. J. F. Lucas
Radboud University, Nijmegen


For many years, it has been recognized that even the best radiologists make errors when reading medical exams including perception failures and interpretation failures. To reduce these problems, computer aided detection and diagnosis systems have been designed to aid radiologists detecting and classifying abnormalities. The first part of this thesis concerns combining information from multiple mammographic projection views to improve detection performance of computer aided detection systems. Most computer-aided detection systems that are used in the clinic today are focussed on reducing perception errors. The research presented in the second part of this thesis investigates if presenting CAD results in a fundamentally different way to avoid interpretation errors is more effective than current computer aided detection methods that focus on preventing perceptual oversights in medical screening.

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