CVNov 27, 2020
Lightweight U-Net for High-Resolution Breast Imaging
arXiv:2011.13698v1
AI Analysis
This work addresses the problem of efficient and accurate malignancy detection for breast cancer screening, but its incremental contribution is unclear without concrete results.
This paper explores fully convolutional neural networks for malignancy detection in breast cancer screening, focusing on supervised segmentation. The goal is to balance network precision with computational complexity, though no specific results or numbers are provided.
We study the fully convolutional neural networks in the context of malignancy detection for breast cancer screening. We work on a supervised segmentation task looking for an acceptable compromise between the precision of the network and the computational complexity.