Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique

Sebastian Hoffmann, Jamie D. Shutler, Marc Lobbes, Bernhard Burgeth, Anke Meyer-Baese*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Web of Science)


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.
Original languageEnglish
Article number172
JournalEurasip Journal on Advances in Signal Processing
Publication statusPublished - 15 Nov 2013


  • Non-mass-enhancing lesions
  • Writhe number
  • Krawtchouk moments
  • Zernike velocity moments
  • Kinetics
  • Classification
  • Computer-aided diagnosis
  • Breast magnetic resonance imaging

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