PSF-SRDN: Point Spread Function-Aware Speckle Reducing Diffusion Network

Ultrasound images are corrupted by signal-dependent speckle, degrading the image quality and presenting challenges for downstream tasks such as segmentation and classification. The ultrasound transducer, as modeled by the point spread function (PSF), further distorts the speckle and the signal. The PSF has different lateral and axial distortions which should be considered in the design of efficient speckle removal methods. To this end, we propose a novel lateral and axial distortion-aware diffusion network that encodes the spectrum of lateral and axial distortions, thus enabling adaptive denoising of images corrupted with speckle. The distortions have been modeled in the forward and reverse processes of a multiplicative noise-based diffusion model. Extensive experiments on two datasets establish the efficiency of the proposed model over state-of-the-art methods. The code and data are available at https://github.com/soumeeguha/PSF-SRDN.