Skin Lesion Recognition with Class-Hierarchy Regularized Hyperbolic Embeddings

Zhen Yu, Toan Nguyen, Yaniv Gal, Lie Ju, Shekhar S. Chandra, Lei Zhang, Paul Bonnington, Victoria Mar, Zhiyong Wang, Zongyuan Ge

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

4 Citations (Scopus)

Abstract

In practice, many medical datasets have an underlying taxonomy defined over the disease label space. However, existing classification algorithms for medical diagnoses often assume semantically independent labels. In this study, we aim to leverage class hierarchy with deep learning algorithms for more accurate and reliable skin lesion recognition. We propose a hyperbolic network to jointly learn image embeddings and class prototypes. The hyperbola provably provides a space for modeling hierarchical relations better than Euclidean geometry. Meanwhile, we restrict the distribution of hyperbolic prototypes with a distance matrix which is encoded from the class hierarchy. Accordingly, the learned prototypes preserve the semantic class relations in the embedding space and we can predict label of an image by assigning its feature to the nearest hyperbolic class prototype. We use an in-house skin lesion dataset which consists of ∼ 230k dermoscopic images on 65 skin diseases to verify our method. Extensive experiments provide evidence that our model can achieve higher accuracy with less severe classification errors compared to that of models without considering class relations.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2022
Subtitle of host publication25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part I
EditorsLinwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li
Place of PublicationCham Switzerland
PublisherSpringer
Pages594-603
Number of pages10
Edition1st
ISBN (Electronic)9783031164316
ISBN (Print)9783031164361
DOIs
Publication statusPublished - 2022
EventMedical Image Computing and Computer-Assisted Intervention 2022 - Singapore, Singapore
Duration: 18 Sept 202222 Sept 2022
Conference number: 25th
https://link.springer.com/book/10.1007/978-3-031-16434-7 (Proceedings - Part 2)
https://conferences.miccai.org/2022/en/ (Website)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13433 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceMedical Image Computing and Computer-Assisted Intervention 2022
Abbreviated titleMICCAI 2022
Country/TerritorySingapore
CitySingapore
Period18/09/2222/09/22
Internet address

Keywords

  • Class hierarchy
  • Deep learning
  • Hyperbolic geometry
  • Skin lesion recognition

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