activity
20242026
most citedTranslating Electrocardiograms to Cardiac Magnetic Resonance Imaging Useful for Cardiac Assessment and Disease Screening: A Multi-Center Study

3 citations · 3 across the 8 of their papers we have counts for

collaborators

8 papers

eess.AS2026

ReStyle-TTS: Relative and Continuous Style Control for Zero-Shot Speech Synthesis

Haitao Li, Chunxiang Jin, Chenglin Li +3

Zero-shot text-to-speech models can clone a speaker's timbre from a short reference audio, but they also strongly inherit the speaking style present in the reference. As a result,…

cs.CL2025

anyECG-chat: A Generalist ECG-MLLM for Flexible ECG Input and Multi-Task Understanding

Haitao Li, Ziyu Li, Yiheng Mao +3

The advent of multimodal large language models (MLLMs) has sparked interest in their application to electrocardiogram (ECG) analysis. However, existing ECG-focused MLLMs primarily…

cs.CV2025

DC-Seg: Disentangled Contrastive Learning for Brain Tumor Segmentation with Missing Modalities

Haitao Li, Ziyu Li, Yiheng Mao +2

Accurate segmentation of brain images typically requires the integration of complementary information from multiple image modalities. However, clinical data for all modalities may…

cs.CV2025

Phenotype-Guided Generative Model for High-Fidelity Cardiac MRI Synthesis: Advancing Pretraining and Clinical Applications

Ziyu Li, Yujian Hu, Zhengyao Ding +5

Cardiac Magnetic Resonance (CMR) imaging is a vital non-invasive tool for diagnosing heart diseases and evaluating cardiac health. However, the limited availability of large-scale,…

eess.SP2025

FOCAL: Fine-Grained Optimal-Transport-Driven Contrastive Alignment of Language and ECGs with Waveform Enhancement

Haitao Li, Che Liu, Zhengyao Ding +3

Electrocardiograms (ECGs) are essential non-invasive tools for diagnosing cardiovascular diseases. While recent multimodal ECG-Report contrastive learning methods have shown promis…

cs.CL2024

De-biased Multimodal Electrocardiogram Analysis

Haitao Li, Ziyu Li, Yiheng Mao +3

Multimodal large language models (MLLMs) are increasingly being applied in the medical field, particularly in medical imaging. However, developing MLLMs for ECG signals, which are…