FasNet: a hybrid deep learning model with attention mechanisms and uncertainty estimation for liver tumor segmentation on LiTS17

FasNet: a hybrid deep learning model with attention mechanisms and uncertainty estimation for liver tumor segmentation on LiTS17

Abstract Liver cancer, especially hepatocellular carcinoma (HCC), remains one of the most fatal cancers globally, emphasizing the critical need for accurate tumor segmentation to enable timely diagnosis and effective treatment planning. Traditional imaging techniques, such as CT and MRI, rely on man...

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Bibliographic Details
Main Authors: Rahul Singh, Sheifali Gupta, Ahmad Almogren, Ateeq Ur Rehman, Salil Bharany, Ayman Altameem, Jaeyoung Choi
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Deep learning
FasNet
ResNet50
VGG16
Attention mechanisms
Monte Carlo dropout
Online Access:https://doi.org/10.1038/s41598-025-98427-9
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https://doi.org/10.1038/s41598-025-98427-9

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