Targeting Precision with Data Augmented Samples in Deep Learning.

We present two different applications of DL (regression and segmentation) to demonstrate the strength of the proposed strategy. We think that this work will pave the way to a explicit use of data augmentation within the loss function that helps the network to be invariant to small variations of the same input samples, a characteristic that is always required to every application in the medical imaging field. PMID: 32455347 [PubMed]
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - Category: Radiology Tags: Med Image Comput Comput Assist Interv Source Type: research