Neues Paper: Stabilizing Tensor Voting for 3D Curvature Estimation
Das Paper "Stabilizing Tensor Voting for 3D Curvature Estimation" von Victor Alfaro Pérez, Virginie Uhlmann, und Brigitte Forster-Heinlein ist in den Proceedings "Workshop on mathematical modeling and scientific computing" erschienen:
https://easychair.org/publications/paper/ssD6
Abstract: Curvature plays an important role in the function of biological membranes, and is therefore a readout of interest in microscopy data. The PyCurv library established itself as a valuable tool for curvature estimation in 3D microscopy images. However, in noisy images, the method exhibits visible instabilities, which are not captured by the standard error measures. In this article, we investigate the source of these instabilities, provide adequate measures to detect them, and introduce a novel post-processing step which corrects the errors. We illustrate the robustness of our enhanced method over various noise regimes and demonstrate that with our orientation correcting post-processing step, the PyCurv library becomes a truly stable tool for curvature quantification.