ECHOPulse: ECG controlled echocardio-grams video generation

TL;DR

ECHOPulse is a novel ECG-conditioned model that rapidly generates high-quality echocardiogram videos using tokenization and time-series prompts, enhancing automated cardiac assessment and disease monitoring.

Contribution

It introduces the first ECG-conditioned ECHO video generation model that accelerates synthesis and eliminates complex prompts, enabling controllable and efficient synthetic data creation.

Findings

Achieves state-of-the-art quality in ECHO video generation

Demonstrates fast inference with tokenization techniques

Generalizes to other medical imaging modalities

Abstract

Echocardiography (ECHO) is essential for cardiac assessments, but its video quality and interpretation heavily relies on manual expertise, leading to inconsistent results from clinical and portable devices. ECHO video generation offers a solution by improving automated monitoring through synthetic data and generating high-quality videos from routine health data. However, existing models often face high computational costs, slow inference, and rely on complex conditional prompts that require experts' annotations. To address these challenges, we propose ECHOPULSE, an ECG-conditioned ECHO video generation model. ECHOPULSE introduces two key advancements: (1) it accelerates ECHO video generation by leveraging VQ-VAE tokenization and masked visual token modeling for fast decoding, and (2) it conditions on readily accessible ECG signals, which are highly coherent with ECHO videos, bypassing complex conditional prompts. To the best of our knowledge, this is the first work to use time-series prompts like ECG signals for ECHO video generation. ECHOPULSE not only enables controllable synthetic ECHO data generation but also provides updated cardiac function information for disease monitoring and prediction beyond ECG alone. Evaluations on three public and private datasets demonstrate state-of-the-art performance in ECHO video generation across both qualitative and quantitative measures. Additionally, ECHOPULSE can be easily generalized to other modality generation tasks, such as cardiac MRI, fMRI, and 3D CT generation. Demo can seen from \url{https://github.com/levyisthebest/ECHOPulse_Prelease}.