A multi-task framework for breast cancer segmentation and classification in ultrasound imaging
The experimental findings underscore the efficacy of multi-task techniques, showcasing better generalization capabilities when considering all image types: benign, malignant, and non-tumor images. Consequently, our methodology represents an advance towards more general architectures with real clinical applications in the breast cancer field.
Authors
- Carlos Aumente-Maestro (ORCID: https://orcid.org/0000-0002-3710-3308)
- Jorge Díez (ORCID: https://orcid.org/0000-0002-1314-2441)
- Beatriz Remeseiro (ORCID: https://orcid.org/0000-0001-9265-253X)
Institutions
- Universidad de Oviedo (ES)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1016/j.cmpb.2024.108540
- Citations
- 27
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 9.38