DPM-LVSN: A Diffusion Probabilistic Model-based Left Ventricular Segmentation Network

Jia Luo; Yuhao Zhong; Yi Ding; Chenghao Zhou; Minghui Pang

ICASSP 2025accepted0 citations

DPM-LVSN: A Diffusion Probabilistic Model-based Left Ventricular Segmentation Network

Jia Luo, Yuhao Zhong, Yi Ding, Chenghao Zhou, Minghui Pang

Abstract

To improve the accuracy and robustness of left ventricular segmentation, This paper proposes a diffusion probabilistic model-based left ventricular segmentation network (DPM-LVSN). DPM-LVSN integrates a U-shaped encoder-decoder for feature extraction, self-attention for semantic information, and a diffusion model for noise recovery. And the efficiency is improved by using feature fusion based on Fourier transform and time step fusion based on confidence. The experimental results on EchoNet-Dynamic dataset show the effectiveness of the proposed method

BibTeX

@inproceedings{icassp2025_dpmlvsnadiffusio,
  title = {DPM-LVSN: A Diffusion Probabilistic Model-based Left Ventricular Segmentation Network},
  author = {Jia Luo and Yuhao Zhong and Yi Ding and Chenghao Zhou and Minghui Pang},
  booktitle = {ICASSP 2025},
  year = {2025}
}