FocusNet++ : Attentive Aggregated Transformations for Efficient and Accurate Medical Image Segmentation

Kaul, Chaitanya, Pears, N. E. orcid.org/0000-0001-9513-5634, Dai, Hang et al. (2 more authors) (2021) FocusNet++ : Attentive Aggregated Transformations for Efficient and Accurate Medical Image Segmentation. In: 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI):. IEEE International Symposium on Biomedical Imaging, 2021, 13-16 Apr 2021 , FRA .

Abstract

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Authors/Creators:
Keywords: Group Ateention, Medical Image Segmentation, Residual Learning
Dates:
  • Accepted: 8 January 2021
  • Published: 25 May 2021
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Pure (York)
Date Deposited: 26 Aug 2022 10:50
Last Modified: 08 Dec 2022 00:07
Published Version: https://doi.org/10.1109/ISBI48211.2021.9433918
Status: Published
Refereed: No
Identification Number: https://doi.org/10.1109/ISBI48211.2021.9433918

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