S-Net: a multiple cross aggregation convolutional architecture for automatic segmentation of small/thin structures for cardiovascular applications

S-Net: a multiple cross aggregation convolutional architecture for automatic segmentation of small/thin structures for cardiovascular applications

With the success of U-Net or its variants in automatic medical image segmentation, building a fully convolutional network (FCN) based on an encoder-decoder structure has become an effective end-to-end learning approach. However, the intrinsic property of FCNs is that as the encoder deepens, higher-l...

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Bibliographic Details
Main Authors: Nan Mu, Zonghan Lyu, Mostafa Rezaeitaleshmahalleh, Cassie Bonifas, Jordan Gosnell, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-11-01
Series:Frontiers in Physiology
Subjects:
automatic segmentation
cardiac wall
intracranial aneurysm (IA)
small/thin structure
fully convolutional network (FCN)
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2023.1209659/full

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https://www.frontiersin.org/articles/10.3389/fphys.2023.1209659/full

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