Dissertation Abstract

Auditory sensory feedback tool to supplement visual data perception in radiologic imaging: A demonstration using MR mammography

To complement and support the scientific visualization methods currently used for conveying all useful morphological, functional and parametric spatial information from the vast amount of complex medical imaging data set, the visual based image analysis combined with auditory sensory information is proposed. IDL software, a sound card and speakers, and a dynamically loadable sound module communicating between the hardware device and our application environments are used for implementation. Clinical sound information efficacy is experimented with three radiologists and 8 DCE-MRI data sets over two different sensory modes (visual+audio, visual only), repeatability is measured, and a statistical hypothesis test is conducted. The visual plus audio mode is more repeatable than that of visual only mode in inter-observer repeatability measurement for difficult tumors. Adding sound information into visual based image analysis is expected to provide more detailed, more accurate and more effective way of analyzing complex multidimensional/multiparametric medical image data sets especially with visually hard cases (lesions).

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