Quantitative Assessments for Ultrasound Probe Calibration
Published in Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021
Recommended citation: Chen ECS, Ma, B, Peters TM, (2021). "Quantitative Assessments for Ultrasound Probe Calibration"; in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2021, LNCS 12904, pp. 363–372. https://doi.org/10.1007/978-3-030-87202-1_35
Ultrasound probe calibration remains an area of active research, but the science of validation has not received proportional attention in current literature. In this paper, we propose a framework to improve, assess, and visualize the quality of probe calibration. The basis of our framework is a heteroscedastic fiducial localization error (FLE) model that is physically quantifiable, used to i) derive an optimal calibration transform in the presence of heteroscedastic FLE, ii) assess the quality of a particular instance of probe calibration using a registration circuit, and iii) visualize the distribution of target registration error (TRE). The novelty of our work is the extension of the registration circuit to Procrustean point-line registration, and a demonstration that it produces a quantitative metric that correlates with true TRE. By treating ultrasound calibration as a heteroscedastic errors-in-variables regression instead of a least-squares regression, a more accurate calibration can be consistently obtained. Our framework has direct implication to many calibration techniques using point- and line-based calibration phantoms.