Abstract
We have implemented an effective and publicly available tool, VETOT, to track and quantify the evolution of tumors and organs over time. VETOT includes a framework both for registration and segmentation. We have evaluated the accuracy and reliability of different level set segmentation methods in order to validate this part of our software and evaluate its usability. In addition to the registration and segmentation frameworks, our program allows the creation of inter- and intra-patient atlases based on a common coordinate system defined by the landmarks selected during the registration process. Based on the National Library of Medicine’s Insight toolkit, this free software is extensible and provides an intuitive interface that allows very fast processing with minimum training. This paper details VETOT and our level set segmentation evaluation.
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Keywords
- Volume Estimation
- Rigid Registration
- Smoothness Constraint
- Deformable Registration
- Geodesic Active Contour
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Guyon, JP. et al. (2003). VETOT, Volume Estimation and Tracking Over Time: Framework and Validation. 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_18
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DOI: https://doi.org/10.1007/978-3-540-39903-2_18
Publisher Name: Springer, Berlin, Heidelberg
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