Interactive, knowledge-guided visualization of 3D medical imagery

Abstract One of the most important and difficult decision-making tasks is that of interpreting three-dimensional (3D) medical imagery. This information-intensive task typically requires expediency, accuracy and reliability in both the visual presentation as well as in the interpretation of complex information. We present an approach that facilitates this task by using domain knowledge to assist in the interpretation and visualization of 3D cardiac imagery. The objective is to provide the clinician with a more efficient, reliable, comprehensive, and clinically useful manner with which to accurately interpret and display large amounts of complex information. These objectives are met by capturing and representing the visual reasoning process in a computational model, and providing the user with an intuitive graphical and textual representation of the data, as well as explanations, justifications, and interactive data visualizations. The approach is illustrated with cardiovascular 3D SPECT tomographic perfusion imagery, a technique aimed at diagnosing heart disease.

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