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Bone surface delineation in ultrasound is of interest due to its potential indiagnosis, surgical planning, and post-operative follow-up in orthopedics, aswell as the potential of using bones as anatomical landmarks in surgicalnavigation. We herein propose a method to encode the physics of ultrasoundpropagation into a factor graph formulation for the purpose of bone surfacedelineation. In this graph structure, unary node potentials encode the locallikelihood for being a soft tissue or acoustic-shadow (behind bone surface)region, both learned through image descriptors. Pair-wise edge potentialsencode ultrasound propagation constraints of bone surfaces given their largeacoustic-impedance difference. We evaluate the proposed method in comparisonwith four earlier approaches, on in-vivo ultrasound images collected fromdorsal and volar views of the forearm. The proposed method achieves an averageroot-mean-square error and symmetric Hausdorff distance of 0.28mm and 1.78mm,respectively. It detects 99.9% of the annotated bone surfaces with a meanscanline error (distance to annotations) of 0.39mm.

Delineating Bone Surfaces in B-Mode Images Constrained by Physics of Ultrasound Propagation