Unified Mixture-of-Experts Framework for Joint Cardiac and Vascular Ultrasound Analysis and Report Generation

Authors

  • Bin Pu Hunan University
  • Jiewen Yang The Hong Kong University of Science and Technology
  • Xingguo Lv Hunan University
  • Kai Xu Yunnan University
  • Kenli Li Hunan University

DOI:

https://doi.org/10.1609/aaai.v40i10.37794

Abstract

Echocardiography and vascular ultrasound are essential for comprehensive cardiovascular assessment, yet manual evaluation and writing reports are labor-intensive, time-consuming, and require expertise from both cardiology and vascular surgery departments. Current automated report generation systems mainly focus on X-ray or CT, often neglecting echocardiographic modalities and critical quantitative parameters like aortic diameter and main pulmonary artery diameter, limiting their clinical utility. Moreover, the interdependence between cardiac and peripheral vascular health necessitates cross-departmental insights, which existing methods fail to incorporate. To address these limitations, we first propose the vision-language framework named the Echo-Cardiac-Vascular (ECV), for joint cardiac and vascular ultrasound report generation and parameter measurements. ECV introduces a Mixture-of-Experts vision encoder tailored for distinct ultrasound subtypes, a structured parameter measurement module for accurate quantification, and task-specific decoders that generate interpretable, multimodal diagnostic reports. Our framework, trained on 10K+ paired records, achieves high accuracy, improving diagnostic efficiency, consistency, and cross-disciplinary clinical applicability.

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Published

2026-03-14

How to Cite

Pu, B., Yang, J., Lv, X., Xu, K., & Li, K. (2026). Unified Mixture-of-Experts Framework for Joint Cardiac and Vascular Ultrasound Analysis and Report Generation. Proceedings of the AAAI Conference on Artificial Intelligence, 40(10), 8439-8447. https://doi.org/10.1609/aaai.v40i10.37794

Issue

Section

AAAI Technical Track on Computer Vision VII