Until recently, segmentation required large, compute-intensive neural networks. This made it difficult to run these deep learning models without a connection to cloud servers. In their latest ...

This paper proposes an end-to-end trained fully convolutional neural network model to process 3D image volumes ... the fast and superior performance of the algorithm on the segmentation of prostate ...

A deep learning (DL)–based model achieved a high ... developed a DL-based tool using the neural network U-Net (nnU-Net) architecture for the automated segmentation of retrospectively collected ...

Transformer-XL aims to make long-range dependence more practical in neural networks ... the previous segment are fixed and cached to be reused as an extended context when the model processes ...