Abstract
This paper presents an approach to semiautomatic segmentation over a time series without the use of a priori geometric anatomical knowledge, and demonstrates its applicability to pericardial effusion segmentation from ultrasound. The described technique solves the problem in two stages, first automatically calculating a set of exclusion zones, then leveraging the surgeon’s anatomical knowledge, simply and interactively, to create a region which corresponds to the stable region within the target effusion. In preliminary testing, the system performs well versus manual segmentation, outperforming it both in terms of perceived quality, as measured in a blinded comparison by an expert, and in terms of time required for generation.
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Bzostek, A., Ionescu, G., Carrat, L., Barbe, C., Chavanon, O., Troccaz, J. (1998). Isolating moving anatomy in ultrasound without anatomical knowledge: Application to computer-assisted pericardial punctures. In: Wells, W.M., Colchester, A., Delp, S. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI’98. MICCAI 1998. Lecture Notes in Computer Science, vol 1496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056293
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DOI: https://doi.org/10.1007/BFb0056293
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