Towards Bone Aware Image Enhancement in Musculoskeletal Ultrasound Imaging

Abstract

Musculoskeletal (MSK) ultrasound imaging aims to provide pictures of tissues and bones such as muscles, tendons, ligaments, joints and soft tissues throughout the body. One of the major landmarks in MSK ultrasound are the bones, and segmentation of bone surface has numerous applications in computer-aided orthopedic diagnosis. In this work, a novel method of bone aware image enhancement of MSK ultrasound images is presented. A combination of fundamental and harmonic US images is used for bone segmentation. The method for bone segmentation takes into account the acoustic characteristics of the intensity of bones used for computing their acoustic shadows, local phase-based features such as local energy, local phase, and feature symmetry based on a reported work in literature. It is combined with integrated backscattering of the bone to provide a probability map of the bone. Bone location in probability map was found based on the centroid of the intensity distribution. Further, image enhancement of the extracted region of interest based on the bone for distinctive visualization of the muscular and tendon region above the bone structure is presented. The image enhancement techniques employed are gamma correction, histogram equalization, adaptive histogram equalization and an improved frequency based super-resolution of ultrasound images.