Analysis of Current Deep Learning Networks for Semantic Segmentation of Anatomical Structures in Laparoscopic Surgery-Reference-Cited by-同舟云学术

Analysis of Current Deep Learning Networks for Semantic Segmentation of Anatomical Structures in Laparoscopic Surgery

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Silva Bruno¹,Oliveira Bruno²,Morais Pedro²,Buschle L.R³,Correia-Pinto Jorge⁴,Lima Estevao⁴,Vilaca Joao L²

Affiliation:

1. Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal,ICVS/3B's- PT Government Associate Laboratory,Braga,Guimaraes,Portugal

2. 2Ai -School of Technology, IPCA,Barcelos,Portugal

3. KARL STORZ SE & Co. KG,Tuttlingen,Germany

4. Government Associate Laboratory, ICVS/3B's-PT,Braga,Guimarães,Portugal

Funder

European Regional Development Fund (FEDER)

FCT (Fundação para a Ciência e a Tecnologia)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871583.pdf?arnumber=9871583

Reference26 articles.

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2. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

3. Local Relation Networks for Image Recognition

4. TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation

5. UNETR: Transformers for 3D Medical Image Segmentation

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