Augmented Active Shape Model Search – towards 3D Ultrasound-based Bone Surface Reconstruction

EPiC series in health sciences, vol. 4, pp. 117–111

Abstract

Patient-specific instrumentation in total knee arthroplasty (TKA), among other medical indications, requires a three-dimensional model of the bones involved. Currently, these are typically segmented from computer tomography images. Ultrasound offers a cheap as well as radiation-less imaging alternative, but suffers from a low signal-to-noise ratio as well as several other image artifacts. The interleaved partial active shape models search (IPASM) adapts a general physiological model to a set of images of a single patient, but suffers from false correspondences being soft tissue interfaces that are interpreted as bone surface. In order to counter this problem, a convolutional neural network (CNN) is applied to preprocess ultrasound images into bone confidence maps. This reduces the average surface distance error in an in-vivo evaluation by 0.7 to 1.3 mm.

Authors 2

1. Benjamin Hohlmann Aachen Chair of Medical Engineering

   RWTH Aachen University

   Affiliation as printed

   Chair of Medical Engineering , Helmholtz-Institute f. BME , RWTH Aachen University of Technology , Aachen , Germany

   Chair of Medical Engineering, Helmholtz-Institute f. BME, RWTH Aachen University of Technology, Aachen, Germany

2. Klaus Radermacher Aachen Chair of Medical Engineering

   RWTH Aachen University

   Affiliation as printed

   Chair of Medical Engineering , Helmholtz-Institute f. BME , RWTH Aachen University of Technology , Aachen , Germany

   Chair of Medical Engineering, Helmholtz-Institute f. BME, RWTH Aachen University of Technology, Aachen, Germany