Back to search

Article

DTA-UNet: U-Net Based on Dynamic Convolution Decomposition and Triplet Attention

2023-09-25

Abstract excerpt

Medical image segmentation methods can assist doctors to quantify and diagnose lesions faster, and give more accurate treatment plans. However, in practical clinical applications, the robustness and generalization ability of medical image segmentation models are challenging due to the differences between different disease types, different image types and different cases. Although U-Net is a universal segmentation...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
f3346ebb-fb3b-5a46-8269-58e01865d6f6
DOI
10.21203/rs.3.rs-3362784/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
DTA-UNet: U-Net Based on Dynamic Convolution Decomposition and Triplet AttentionDOI 10.21203/rs.3.rs-3362784/v1
Select a neighboring publication to make it the new centre.