Freehand ultrasound reconstruction based on ROI prior modeling and normalized convolution

Abstract

3D freehand ultrasound imaging is becoming a widespread technique in medical examinations. This imaging technique produces a set of irregularly spaced B-scans. Reconstructing a regular grid from these B-scans is a challenging problem that enables the visualization and further analysis of the acquired data. This paper focuses on extending an existing method [1] to define the output reconstruction grid based on principal component analysis (PCA). Our method introduces a model for the region of interest (ROI) in order to adapt the grid to the ROI. In addition, a technique based on normalized convolution is proposed for the interpolation problem. A new applicability function based on the correlation function of a linear probe is used to avoid inter-resolution cell blurring.