Dealing with Unreliable Annotations: A Noise-Robust Network for Semantic Segmentation through A Transformer-Improved Encoder and Convolution Decoder

Dealing with Unreliable Annotations: A Noise-Robust Network for Semantic Segmentation through A Transformer-Improved Encoder and Convolution Decoder

Conventional deep learning methods have shown promising results in the medical domain when trained on accurate ground truth data. Pragmatically, due to constraints like lack of time or annotator inexperience, the ground truth data obtained from clinical environments may not always be impeccably accu...

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Bibliographic Details
Main Authors: Ziyang Wang, Irina Voiculescu
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Applied Sciences
Subjects:
image segmentation
noisy label
computed tomography
Vision Transformer
Online Access:https://www.mdpi.com/2076-3417/13/13/7966

Internet

https://www.mdpi.com/2076-3417/13/13/7966

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