Volumetric ultrasound and computer-assisted analysis at the point-of-care: a musculoskeletal exemplar.

In this paper we motivate the hypothesis that the use of volumetric ultrasound imaging and automated image analysis tools would improve clinical workflows as well as outcomes at the point-of-care. To make our case, this paper presents results from a rheumatoid arthritis (RA) study where several image analysis techniques have been applied to volumetric ultrasound, highlighting anatomy of interest to better understand disease progression. Pathologies related to RA in joints, manifest themselves commonly as changes in the bone (e.g. erosions) and the region enclosed by the joint-capsule (e.g. synovitis). Automated tools for detecting and segmenting such structures would help significantly towards objective and quantitative assessment of RA in joints. Extracted bone coupled with a simple anatomical model of the joint provides a coarse localization of the joint-capsule region. A probabilistic speckle model is then used to iteratively refine the capsule segmentation. We illustrate the performance of proposed algorithms through quantitative comparisons with expert annotations as well as qualitative results on over 30 scans obtained from 11 subjects.