A dilated residual hierarchically fashioned segmentation framework for extracting Gleason tissues and grading prostate cancer from whole slide images

Taimur Hassan, Bilal Hassan, Ayman ElBaz, Naoufel Werghi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Prostate cancer (PCa) is the second deadliest form of cancer in males, and it can be clinically graded by examining the structural representations of Gleason tissues. This paper proposes a new method for segmenting the Gleason tissues (patch-wise) in order to grade PCa from the whole slide images (WSI). Also, the proposed approach encompasses two main contributions: 1) A synergy of hybrid dilation factors and hierarchical decomposition of latent space representation for effective Gleason tissues extraction, and 2) A three-tiered loss function which can penalize different semantic segmentation models for accurately extracting the highly correlated patterns. In addition to this, the proposed framework has been extensively evaluated on a large-scale PCa dataset containing 10,516 whole slide scans (with around 71.7M patches), where it outperforms state-of-the-art schemes by 3.22% (in terms of mean intersection-over-union) for extracting the Gleason tissues and 6.91% (in terms of F1 score) for grading the progression of PCa.

Original languageBritish English
Title of host publication2021 IEEE Sensors Applications Symposium, SAS 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728194318
DOIs
StatePublished - 23 Aug 2021
Event2021 IEEE Sensors Applications Symposium, SAS 2021 - Virtual, Sundsvall, Sweden
Duration: 23 Aug 202125 Aug 2021

Publication series

Name2021 IEEE Sensors Applications Symposium, SAS 2021 - Proceedings

Conference

Conference2021 IEEE Sensors Applications Symposium, SAS 2021
Country/TerritorySweden
CityVirtual, Sundsvall
Period23/08/2125/08/21

Keywords

  • Dice loss
  • Focal tversky loss
  • Gleason patterns
  • Prostate cancer

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