An automated segmentation technique for the processing of foot ultrasound images

Abstract

In spite of the advantages of ease of imaging and low acquisition cost, ultrasound images are noisier and have poorer image quality than other imaging modalities like CT or MRI and hence require an experienced clinician for interpretation. Processing by automated segmentation assists clinicians and improves the accuracy of assessment by minimizing its subjective nature. Various methods for the segmentation of ultrasound images exist, but there is not much literature on the processing of 2D ultrasound images of the foot. This work aimed at developing a novel method for image processing in order to achieve automated segmentation of ultrasound images of the plantar soft tissue. Preprocessing of the ultrasound images was performed using the anisotropic diffusion filter followed by contrast enhancement. The Chan-Vese active contour method was used for segmentation. Our method took into account the difficulty of visualization of the tissues and bony structures in the foot and used an additional curvature parameter for segmentation. Assessing the changes in the biomechanical properties of the plantar soft tissue can be a potential application of this method especially in case of the diabetic foot.