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.
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Estépar, R.S.J., Martín-Fernández, M., Alberola-López, C., Ellsmere, J., Kikinis, R., Westin, CF. (2003). Freehand Ultrasound Reconstruction Based on ROI Prior Modeling and Normalized Convolution. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39903-2_47
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DOI: https://doi.org/10.1007/978-3-540-39903-2_47
Publisher Name: Springer, Berlin, Heidelberg
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