Abstract
Three-dimensional (3D) shape lies at the core of understanding the physical objects that surround us. In the biomedical field, shape analysis has been shown to be powerful in quantifying how anatomy changes with time and disease. The Shape AnaLysis Toolbox (SALT) was created as a vehicle for disseminating advanced shape methodology as an open source, free, and comprehensive software tool. We present new developments in our shape analysis software package, including easy-to-interpret statistical methods to better leverage the quantitative information contained in SALT’s shape representations. We also show SlicerPipelines, a module to improve the usability of SALT by facilitating the analysis of large-scale data sets, automating workflows for non-expert users, and allowing the distribution of reproducible workflows.
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Acknowledgements
SlicerSALT development has been funded by NIH NIBIB awards R01EB021391 and R56EB021391 as well as NHLBI award R01HL153166.
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Vicory, J. et al. (2023). SlicerSALT: From Medical Images to Quantitative Insights of Anatomy. In: Wachinger, C., Paniagua, B., Elhabian, S., Li, J., Egger, J. (eds) Shape in Medical Imaging. ShapeMI 2023. Lecture Notes in Computer Science, vol 14350. Springer, Cham. https://doi.org/10.1007/978-3-031-46914-5_16
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DOI: https://doi.org/10.1007/978-3-031-46914-5_16
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