Sep 2, 2020 · Here we present MoNet, a highly optimized neural-network-based pancreatic segmentation algorithm focused on achieving high performance by efficient multi-scale ...
Efficient, high-performance semantic segmentation using multi-scale ...
pubmed.ncbi.nlm.nih.gov › ...
Here we present MoNet, a small, highly optimized neural-network-based segmentation algorithm leveraging efficient multi-scale image features.
MoNet is presented, a highly optimized neural-network-based pancreatic segmentation algorithm focused on achieving high performance by efficient multi-scale ...
Here we present MoNet, a small, highly optimized neural-network-based segmentation algorithm leveraging efficient multi-scale image features.
Here we present MoNet, a highly optimized neural-network-based pancreatic segmentation algorithm focused on achieving high performance by efficient multi-scale ...
For artificial intelligence-based image analysis methods to reach clinical applicability, the development of high-performance algorithms is crucial.
Aug 19, 2021 · We showcase our architecture's performance on the challenging task of pancreatic segmentation as well as brain tumor segmentation and ...
Aug 30, 2024 · Here we present MoNet, a small, highly optimized neural-network-based segmentation algorithm leveraging efficient multi-scale image features.
We report performance on validation sets of the MSD datasets (brain tumor and pancreas) as well as out-of sample generalization performance on an independent ...
MoNet is a shallow, U-Net-like architecture based on repeated, dilated convolutions with decreasing dilation rates. We apply and test our architecture on the ...