DiffPWI: A degradation-aware diffusion model for ultrasound plane-wave imaging.
Authors
Affiliations (5)
Affiliations (5)
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
- Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China.
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China. Electronic address: [email protected].
- Shenzhen Key Laboratory of Ultrasound Imaging and Therapy, State Key Laboratory of Biomedical Imaging Science and System, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen 518055, China. Electronic address: [email protected].
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China. Electronic address: [email protected].
Abstract
Ultrafast plane-wave imaging (PWI) trades image quality for frame rate under sparse acquisitions. Existing deep learning-based PWI reconstruction methods are limited by the lack of physics-guided degradation modeling, leading to distortions in anatomical structures and speckle statistics. In addition, an inherent low-frequency spectral bias attenuates high-frequency components, further exacerbating detail loss and amplifying reconstruction artifacts. In this study, we propose DiffPWI, a degradation-aware reconstruction framework. DiffPWI employs a latent diffusion model (LDM) to learn the distribution of physically informed degradations in a compressed latent space, providing a physics-informed prior for reconstruction. Furthermore, we introduce a frequency decoupling attention module (FDAM) that adaptively decomposes feature representations into hierarchical frequency sub-bands, enabling preservation of high-frequency anatomical details while suppressing acquisition artifacts. Extensive evaluations on phantom, multi-organ in vivo, and zero-shot datasets demonstrate that DiffPWI achieves improved spatial resolution, contrast recovery, and speckle fidelity compared with state-of-the-art methods, advancing high-fidelity ultrafast ultrasound imaging.