DPM-LVSN:A Diffusion Probabilistic Model-based Left Ventricular Segmentation Network
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
Authors
- Yi Ding
- Yuhao Zhong (ORCID: https://orcid.org/0000-0002-2560-3911)
- Chenhao Zhou (ORCID: https://orcid.org/0000-0002-4800-3249)
- Minghui Pang (ORCID: https://orcid.org/0009-0003-9705-8443)
- Jia Luo (ORCID: https://orcid.org/0000-0003-2248-7983)
Institutions
- University of Electronic Science and Technology of China (CN)
Publication Details
- Published
- 2025-03-12
- DOI
- https://doi.org/10.1109/icassp49660.2025.10888748
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Baidu
- National Natural Science Foundation of China
- University of Electronic Science and Technology of China