S137 - Improving Mammography Malignancy Segmentation by Designing the Training Process

Mickael Tardy, Diana Mateus

Show abstract - Show schedule - PDF - Reviews - Teaser

We work on the breast imaging malignancy segmentation task while focusing on the train- ing process instead of network complexity. We designed a training process based on a modified U-Net, increasing the overall segmentation performances by using both, benign and malignant data for training. Our approach makes use of only a small amount of anno- tated data and relies on transfer learning from a self-supervised reconstruction task, and favors explainability.
Hide abstract

Poster Session #5 - 9:30 - 11:00 UTC-4 (Wednesday)
Hide schedule

Access paper channel


Short paper


Can't display slides, your browser doesn't support embedding PDFs. You can still download the slides:

Download slides