1 research outputs found
Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique
Abstract
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) represents an established method for the
detection and diagnosis of breast lesions. While mass-like enhancing lesions can be easily categorized according to
the Breast Imaging Reporting and Data System (BI-RADS) MRI lexicon, a majority of diagnostically challenging lesions,
the so called non-mass-like enhancing lesions, remain both qualitatively as well as quantitatively difficult to analyze.
Thus, the evaluation of kinetic and/or morphological characteristics of non-masses represents a challenging task for
an automated analysis and is of crucial importance for advancing current computer-aided diagnosis (CAD) systems.
Compared to the well-characterized mass-enhancing lesions, non-masses have no well-defined and blurred tumor
borders and a kinetic behavior that is not easily generalizable and thus discriminative for malignant and benign
non-masses. To overcome these difficulties and pave the way for novel CAD systems for non-masses, we will evaluate
several kinetic and morphological descriptors separately and a novel technique, the Zernike velocity moments, to
capture the joint spatio-temporal behavior of these lesions, and additionally consider the impact of non-rigid motion
compensation on a correct diagnosis.
Keywords:
Non-mass-enhancing lesions; Writhe number; Krawtchouk moments; Zernike velocity moments; Kinetics;
Classification; Computer-aided diagnosis; Breast magnetic resonance imagin