Enhancing Breast Ultrasound Diagnosis: A DCNN-Based Approach for Lesion Detection and Segmentation
Introduction: Breast cancer remains the most prevalent cancer among women, making early detection critical for reducing mortality rates. Ultrasound imaging is a valuable diagnostic tool due to its accessibility and non-invasiveness; however, its accuracy depends heavily on the expertise of the sonographers, [for full text, please go to the a.m. URL]
Authors
- Lotta Ada Fischer
- Wolfram Malter (ORCID: https://orcid.org/0000-0002-5693-3120)
- Christian Eichler (ORCID: https://orcid.org/0000-0003-0675-8202)
- Mathias Warm (ORCID: https://orcid.org/0000-0002-5330-1902)
- Fatma Alickovic
- Wim van de Vooren
- Tamsila Khan
Institutions
- University of Cologne (DE)
- Johannes Gutenberg University Mainz (DE)
- Düsseldorf University Hospital (DE)
- University Medical Center of the Johannes Gutenberg University Mainz (DE)
- St. Franziskus Hospital (DE)
- Krankenhaus Köln-Holweide (DE)
- Heinrich Heine University Düsseldorf (DE)
Publication Details
- Journal
- German Medical Science (German Research Foundation)
- Published
- 2026-04-01
- DOI
- https://doi.org/10.3205/25gmds188
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00