Hoffmann, Sebastian and Shutler, Jamie D. and Lobbes, Marc and Burgeth, Bernhard and Meyer-Baese, Anke (2013) Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique. EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING: 172. ISSN 1687-6180,
Full text not available from this repository. (Request a copy)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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | THEORETIC CAD-SYSTEM; CARCINOMA IN-SITU; NEURAL-NETWORKS; IMAGE-ANALYSIS; DCE-MRI; DIAGNOSIS; ENHANCEMENT; CANCER; INFORMATION; MAMMOGRAPHY; Non-mass-enhancing lesions; Writhe number; Krawtchouk moments; Zernike velocity moments; Kinetics; Classification; Computer-aided diagnosis; Breast magnetic resonance imaging |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 26 Mar 2020 10:01 |
| Last Modified: | 26 Mar 2020 10:01 |
| URI: | https://pred.uni-regensburg.de/id/eprint/15669 |
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