Non-mass enhancing lesions represent one of the most challenging types of lesions when it comes to both manual and computer-assisted diagnosis. Compared to the well-characterized mass-enhancing lesions, non-masses have not well-defined and blurred tumor borders and a kinetic behavior that is not easily generalizable and thus non-discriminative for malignant and benign non-masses. A valuable feature descriptor should capture the heterogeneity of enhancement as well as the speed of enhancement in the tissue. We apply and evaluate both textural and spatio-temporal descriptors to the pertinent feature extraction of these lesions. An automated computer-aided diagnosis system evaluates the atypical behavior of these lesions, and additionally considers the impact of non-rigid motion compensation on a correct diagnosis.

Date Published: 29 May 2013
PDF: 8 pages
Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 875009 (29 May 2013);

Published in SPIE Proceedings Vol. 8750:
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
Harold H. Szu, Editor(s)