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Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique
Hoffmann, Sebastian, Shulter, Jamie, Lobbes, Marc, Burgeth, Bernhard und Meyer-Bäse, 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 2013, S. 172.
Veröffentlichungsdatum dieses Volltextes: 12 Feb 2014 10:02
Artikel
DOI zum Zitieren dieses Dokuments: 10.5283/epub.29506
Zusammenfassung
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 ...
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.
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| Dokumentenart | Artikel | ||||
| Titel eines Journals oder einer Zeitschrift | EURASIP Journal on Advances in Signal Processing | ||||
| Verlag: | SPRINGER INTERNATIONAL PUBLISHING AG | ||||
|---|---|---|---|---|---|
| Ort der Veröffentlichung: | CHAM | ||||
| Band: | 2013 | ||||
| Seitenbereich: | S. 172 | ||||
| Datum | 2013 | ||||
| Institutionen | Biologie und Vorklinische Medizin > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang | ||||
| Identifikationsnummer |
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| Stichwörter / 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 | ||||
| Dewey-Dezimal-Klassifikation | 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften, Biologie | ||||
| Status | Veröffentlicht | ||||
| Begutachtet | Ja, diese Version wurde begutachtet | ||||
| An der Universität Regensburg entstanden | Ja | ||||
| URN der UB Regensburg | urn:nbn:de:bvb:355-epub-295064 | ||||
| Dokumenten-ID | 29506 |
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