Multi-view Contrastive Learning with Additive Margin for Adaptive Nasopharyngeal Carcinoma Radiotherapy Prediction

Jiabao Sheng, Sai Kit Lam, Zhe Li, Jiang Zhang, Xinzhi Teng, Yuanpeng Zhang, Jing Cai

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

The accurate prediction of adaptive radiation therapy (ART) for nasopharyngeal carcinoma (NPC) patients before radiation therapy (RT) is crucial for minimizing toxicity and enhancing patient survival rates. Owing to the complexity of the tumor micro-environment, a single high-resolution image offers only limited insight. Furthermore, the traditional softmax-based loss falls short in quantifying a model's discriminative power. To address these challenges, we introduce a supervised multi-view contrastive learning approach with an additive margin (MMCon). For each patient, we consider four medical images to form multi-view positive pairs, which supply supplementary information and bolster the representation of medical images. We employ supervised contrastive learning to determine the embedding space, ensuring that NPC samples from the same patient or with the same labels stay in close proximity while NPC samples with different labels are distant. To enhance the discriminative ability of the loss function, we incorporate a margin into the contrastive learning process. Experimental results show that this novel learning objective effectively identifies an embedding space with superior discriminative abilities for NPC images.

Original languageEnglish
Title of host publicationICMR 2023 - Proceedings of the 2023 ACM International Conference on Multimedia Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages555-559
Number of pages5
ISBN (Electronic)9798400701788
DOIs
Publication statusPublished - 12 Jun 2023
Event2023 ACM International Conference on Multimedia Retrieval, ICMR 2023 - Thessaloniki, Greece
Duration: 12 Jun 202315 Jun 2023

Publication series

NameICMR 2023 - Proceedings of the 2023 ACM International Conference on Multimedia Retrieval

Conference

Conference2023 ACM International Conference on Multimedia Retrieval, ICMR 2023
Country/TerritoryGreece
CityThessaloniki
Period12/06/2315/06/23

Keywords

  • Contrastive Learning
  • Medical Image Analysis
  • Multi-view
  • Nasopharyngeal Carcinoma

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Software
  • Computer Graphics and Computer-Aided Design

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