ABSTRACT
Cardiovascular Magnetic Resonance (CMR) imaging is an essential technique for measuring regional myocardial function. However, it is a time-consuming and cognitively demanding task to interpret, identify and compare various motion characteristics based on watching CMR imagery. In this work, we focus on the problems of visualising imagery resulting from 2D myocardial tagging in CMR. In particular we provide an overview of the current state of the art of relevant visualization techniques, and a discussion on why the problem is difficult from a perceptual perspective. Finally, we introduce a proof-of-concept multilayered visualization user interface for visualizing CMR data using multiple derived attributes encoded into multivariate glyphs. An initial evaluation of the system by clinicians suggested a great potential for this visualisation technology to become a clinical practice in the future.
Subject(s)
Heart/anatomy & histology , Heart/physiology , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging, Cine/methods , Myocardial Contraction/physiology , Animals , Humans , Reproducibility of Results , Sensitivity and Specificity , Signal Processing, Computer-Assisted , Spatio-Temporal Analysis , Subtraction Technique , User-Computer InterfaceABSTRACT
Using measurements of real-world samples of metals, the proposed approach verifies predictions of bidirectional reflectance distribution function (BRDF) models. It employs ellipsometry to verify both the actual polarizing effect and the overall reflectance behavior of the metallic surfaces.
