LECANDUS study (LEsion CANdidate Detection in UltraSound Data): evaluation of image analysis algorithms for breast lesion detection in volume ultrasound data
This study aims at developing and evaluating a prototype of a lesion candidate detection algorithm for a 3D-US computer-aided diagnosis (CAD) system.
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| Hauptverfasser: | , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
28 May 2016
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| In: |
Archives of gynecology and obstetrics
Year: 2016, Jahrgang: 294, Heft: 2, Pages: 423-428 |
| ISSN: | 1432-0711 |
| DOI: | 10.1007/s00404-016-4127-5 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/s00404-016-4127-5 |
| Verfasserangaben: | Michael Golatta, Désirée Zeegers, Konstantinos Filippatos, Leah-Larissa Binder, Alexander Scharf, Geraldine Rauch, Joachim Rom, Florian Schütz, Christof Sohn, Joerg Heil |
| Zusammenfassung: | This study aims at developing and evaluating a prototype of a lesion candidate detection algorithm for a 3D-US computer-aided diagnosis (CAD) system. |
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| Beschreibung: | Gesehen am 30.06.2020 |
| Beschreibung: | Online Resource |
| ISSN: | 1432-0711 |
| DOI: | 10.1007/s00404-016-4127-5 |