Dense Correspondence Analysis (DeCA) for 3D surfaces is a toolkit built as an extension to the 3D Slicer Platform.

DeCA is an open-source tool for biologists and other researchers using 3D imaging. DeCA integrates biological insights in the form of homologous landmark points with dense surface registration to provide highly detailed shape analysis of smooth and complex structures that are typically challenging to analyze with sparse manual landmarks alone.

DeCA comprises of three modules: The main DeCA module (with optional asymmetry analysis), DeCAL module for automated landmarking via template, and Visualize Results module to obtain heatmaps of shape and/or asymmetry differences from DeCA.

• Introduction to DeCA
• Asymmetry analysis by DeCA
• DeCAL: Use DeCA for dense pseudo-landmarking of a set of models

1. Rolfe, S. M., Mao, D., & Maga, A. M. (2025). Streamlining Asymmetry Quantification in Fetal Mouse Imaging: A Semi-Automated Pipeline Supported by Expert Guidance. Developmental Dynamics. Early View
2. Rolfe, S.M., Maga, A.M. (2023). DeCA: A Dense Correspondence Analysis Toolkit for Shape Analysis. 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_21

This extension was developed by funding from National Institutes of Health (OD032627 and HD104435)