Edge Enhancing Accelerated Diffusion Model for Speckle Denoising in Medical Imagery

¹ Saginaw Valley State University, USA
² Mississippi State University, USA

^* e-mail: abmisra@svsu.edu
^** e-mail: cdj192@msstate.edu
^*** e-mail: hlim@math.msstate.edu

Abstract

Speckle noise occurs in a wide range of medical images due to sampling and digital degradation. Removing speckle noise from medical images is the key for further automated processing techniques like segmentation, and can help the clinicians with better diagnosis and therapy. We consider partial differential equation (PDE)-based denoising model which is a modified Euler-Lagrange equation derived from the total variation minimization functional with additional speckle noise constraints. The new PDE model is designed and optimized to rectify speckle noise and enhance edges present in medical imagery. Wealso develop the efficicient and stable discretization techniques for the corresponding speckle denoising model. The method is tested for several types of images including ultrasound images, and it is compared favorably to the conventional denoising model.