Computational Framework for Segmentation and Grouping
Computational Framework for Segmentation and Grouping
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Level Set Based Shape Prior Segmentation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Segmentation of heterogeneous blob objects through voting and level set formulation
Pattern Recognition Letters
A Delaunay triangulation approach for segmenting clumps of nuclei
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Multidimensional Profiling of Cell Surface Proteins and Nuclear Markers
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Accurate spatial neighborhood relationships for arbitrarily-shaped objects using Hamilton-Jacobi GVD
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Cell segmentation using coupled level sets and graph-vertex coloring
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Voronoi-Based segmentation of cells on image manifolds
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
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Membrane-bound macromolecules play an important role in tissue architecture and cell-cell communication, and is regulated by almost one-third of the genome. At the optical scale, one group of membrane proteins expresses themselves as linear structures along the cell surface boundaries, while others are sequestered. This paper targets the former group, whose intensity distributions are often heterogeneous and may lack specificity. Segmentation ofthe membrane protein enables the quantitative assessment of localization for comparative analysis. We introduce a three-step process to (i) regularize the membrane signal through iterative tangential voting, (ii) constrain the location of surface proteins by nuclear features, and (iii) assign membrane proteins to individual cells through an application of multi-phase geodesic level-set. We have validated our method against a dataset of 200 images, and demonstrated that multiphase level set has a superior performance compared to gradient vector flow snake.