A Review of Capsule Networks in Medical Image Analysis

Heba El-Shimy*, Hind Zantout, Michael Lones, Neamat El Gayar

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
55 Downloads (Pure)


Computer-aided diagnosis technologies are gaining increased focus within the medical field due to their role in assisting physicians in their diagnostic decision-making through the ability to recognise patterns in medical images. Such technologies started showing promising results in their ability to match or outperform physicians in certain specialities and improve the quality of medical diagnosis. Convolutional neural networks are one state-of-the-art technique to use for disease detection and diagnosis in medical images. However, capsule networks aim to improve over these by preserving part-whole relationships between an object and its sub-components leading to better interpretability, an important characteristic for applications in the medical domain. In this paper, we review the latest applications of capsule networks in computer-aided diagnosis from medical images and compare their results with those of convolutional neural networks employed for the same tasks. Our findings support the use of Capsule Networks over Convolutional Neural Networks for Computer-Aided Diagnosis due to their superiority in performance but more importantly for their better interpretability and their ability to achieve such performance on small datasets.

Original languageEnglish
Title of host publicationArtificial Neural Networks in Pattern Recognition. ANNPR 2022
EditorsNeamat El Gayar, Edmondo Trentin, Mirco Ravanelli, Hazem Abbas
Number of pages16
ISBN (Electronic)9783031206504
ISBN (Print)9783031206498
Publication statusPublished - 2023
Event10th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition 2022 - Dubai, United Arab Emirates
Duration: 24 Nov 202226 Nov 2022

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition 2022
Abbreviated titleANNPR 2022
Country/TerritoryUnited Arab Emirates
Internet address


  • CADx
  • Capsule networks
  • Computer-aided detection
  • Computer-aided diagnosis
  • Deep learning
  • Medical imaging

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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