Abstract
Multimodal learning, integrating histology images and genomics, promises to enhance precision oncology with comprehensive views at microscopic and molecular levels. However, existing methods may not sufficiently model the shared or complementary information for more effective integration. In this study, we introduce a Unified Modeling Enhanced Multimodal Learning (UMEML) framework that employs a hierarchical attention structure to effectively leverage shared and complementary features of both modalities of histology and genomics. Specifically, to mitigate unimodal bias from modality imbalance, we utilize a query-based cross-attention mechanism for prototype clustering in the pathology encoder. Our prototype assignment and modularity strategy are designed to align shared features and minimizes modality gaps. An additional registration mechanism with learnable tokens is introduced to enhance cross-modal feature integration and robustness in multimodal unified modeling. Our experiments demonstrate that our method surpasses previous state-of-the-art approaches in glioma diagnosis and prognosis tasks, underscoring its superiority in precision neuro-Oncology.
Original language | English |
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Title of host publication | Computational Mathematics Modeling in Cancer Analysis |
Subtitle of host publication | Third International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024, Proceedings |
Editors | Jia Wu, Wenjian Qin, Chao Li, Boklye Kim |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 1-10 |
Number of pages | 10 |
Edition | 1 |
ISBN (Electronic) | 9783031733604 |
ISBN (Print) | 9783031733598 |
DOIs | |
Publication status | Published - 5 Oct 2024 |
Event | 3rd Workshop on Computational Mathematics Modeling in Cancer Analysis - Marrakesh, Morocco Duration: 6 Oct 2024 → 6 Oct 2024 https://cmmcaworkshop.github.io/2024/ (Link to Conference) |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 15181 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 3rd Workshop on Computational Mathematics Modeling in Cancer Analysis |
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Abbreviated title | CMMCA 2024 |
Country/Territory | Morocco |
City | Marrakesh |
Period | 6/10/24 → 6/10/24 |
Other | CMMCA 2024 was held in conjunction with the 27th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024 |
Internet address |
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Keywords
- Glioma
- Multimodal classification
- Multimodal learning
- Survival prediction
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science