Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
General Object Reconstruction Based on Simplex Meshes
International Journal of Computer Vision
Exploiting Triangulated Surface Extraction Using Tetrahedral Decomposition
IEEE Transactions on Visualization and Computer Graphics
Coupled Parametric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D mumford-shah based active mesh
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Segmenting and tracking fluorescent cells in dynamic 3-D microscopy with coupled active surfaces
IEEE Transactions on Image Processing
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Recent advances in bioimaging have allowed to observe biological phenomena in three dimensions in a precise and automated fashion. However, the analysis of depth-stacks acquired in fluorescence microscopy constitutes a challenging task and motivates the development of robust methods. Automated computational schemes to process 3D multi-cell images from High Content Screening (HCS) experiments are part of the next generation methods for drug discovery. Working toward this goal, we propose a fully automated framework which allows fast segmentation and 3D morphometric analysis of cell nuclei. The method is based on deformable models called Active Meshes, featuring automated initialization, robustness to noise, real-time 3D visualization of the objects during their analysis and precise geometrical shape measurements thanks to a parametric representation of each object. The framework has been tested on a low throughput microscope (classically found in research facilities) and on a fully automated imaging platform (used in screening facilities). We also propose shape descriptors and evaluate their robustness and independence on fluorescent beads and on two cell lines.