View source for ITK GPAC level set

==Key Investigators==
* University of Missouri: Ilker Ersoy, Filiz Bunyak, K. Palaniappan
* Harvard Medical School: Kishore Mosaliganti, Sean Megason

==Project==
[[File:Multiphase-GPAC-HeLa-segmentation.png|400px|thumb|left|4-phase cell segmentation]]
[[File:MRI-multiphase-gpac.png|400px|thumb|left|4-phase MRI segmentation]]
[[File:Histopathology_mvls_4class.png|400px|thumb|left|Vector 4-phase histopathology segmentation]]
[[File:Histopathology_GVD2_grade4_2_zoom.png |400px|thumb|left|Nuclei detection using multiphase for Grade4 prostate carcinoma]]

[[File:Zebrafish-nuclei-membrane-channel-multiphase.png |400px|thumb|left|4-phase nuclei segmentation result using fused (weighted) nuclei plus membrane channels]]
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<h3>Objective</h3>
Multiphase level sets efficiently segment multiclass multiobject images. Current ITK level sets support the N-level set approach to handle N-objects. Multiphase methods can be applied to a variety of underlying level set energy functions including Chan-Vese, graph partitioning active contours (GPAC), 4-color level sets, and hybrid approaches.

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<h3>Approach, Plan</h3>
Extend the current ITK level set class to handle multiphase level sets with support for two, three or a general number of level sets cases. Multiphase methods model <math>N</math> classes using <math>\log N</math> phases. Each phase can be used to segment any number of objects. We plan to develop a mechanism for multiphase coupling of multichannel data (i.e. nuclear and membrane channels) with scalar or vector-based energy functions.  We plan to include support for 2D and 3D multiphase curve and surface evolution.

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<h3>Progress</h3>
Preliminary multiphase Chan-Vese level set segmentation algorithm has been developed using a Matlab reference implementation. Test cases with synthetic and microscopy imagery have been completed. Need to finish implementation for N-classes, extension to 3D and develop suite of test cases.
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<h3>NA-MIC Progress</h3>
* Finished multiphase implementation and created preliminary test data for validation of results.
* Debugging of multiphase update equations for the general N-level set <math>2^N</math> phase case still continuing.
* Need to add test cases in ITK for specific 4-phase and 8-phase level set evolution.
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==Resources==
* Source code :
 
We shall use [http://git-scm.com/ git] for version control :
A small introduction to git : [http://sourceforge.net/apps/trac/gofigure2/wiki/GIT here]
* Data sets:
 HeLa cell cycle phase analysis from Cristina Cardoso (Technical Univ of Darmstadt). 
 Prostate carcinoma from Michael Feldman (Univ of Pennsylvania).
 Zebrafish embryogenesis 3D confocal multichannel imagery from Sean Megason.
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==Delivery Mechanism==

This work will be delivered as an:

#ITK Module
#Slicer Module (possibly)

==References==
*F. Bunyak, A. Hafiane, K. Palaniappan, Histopathology tissue segmentation by combining fuzzy clustering with multiphase vector level sets. Software Tools and Algorithms for Biological Systems, Springer, 2010. 

*I. Ersoy, F. Bunyak, V. Chagin, M. C. Cardoso, K. Palaniappan, “Segmentation and classification of cell cycle phases in fluorescence imaging”, Lecture Notes in Computer Science (MICCAI), Vol. 5762 (Part II), pp. 617-624, 2009. 

*F. Bunyak, K. Palaniappan, V. Chagin, M. C. Cardoso, "Cell Segmentation in time-lapse fluorescence microscopy with temporally varying sub-cellular fusion protein patterns", 31st Int. Conf. IEEE Engineering in Medicine and Biology Society (EMBC), Minneapolis, Minnesota, Sep. 2009, pp. 1424-1428.

*K. Palaniappan, F. Bunyak, S. Nath, J. Goffeney, “Parallel processing strategies for cell motility and shape analysis”, High-Throughput Image Reconstruction and Analysis, Ed. C.R. Rao and G. A. Cecchi, Artech, Chapter 3, 2009. 

*F. Bunyak, K. Palaniappan, "Level set-based fast graph partitioning active contours using constant memory", Lecture Notes in Computer Science (ACIVS), Vol. 5807, pp. 145-155, 2009. 

*A. Mosig, S. Jaeger, W. Chaofeng, I. Ersoy, S. K. Nath, K. Palaniappan, S.S. Chen, “Tracking cells in live cell imaging videos using topological alignments”, Algorithms in Molecular Biology, Vol. 4, 10p., 2009.

*F. Bunyak, K. Palaniappan, "Efficient segmentation using feature-based graph partitioning active contours", 12th IEEE Int. Conf. Computer Vision (ICCV), Sep. 29-Oct. 2 2009, Kyoto, Japan, pp. 873-880.

*S. K. Nath, K. Palaniappan, “Fast graph partitioning active contours for image segmentation using histograms”, EURASIP Journal on Image and Video Processing, 9p., 2009, Article ID 820986 (doi:10.1155/2009/820986). 

*A. Hafiane, F. Bunyak, K. Palaniappan, “Clustering initiated multiphase active contours and robust separation of nuclei groups for tissue segmentation”, IEEE Int. Conf. Pattern Recognition, 2008.

*A. Hafiane, F. Bunyak, K. Palaniappan, “Fuzzy clustering and active contours for histopathology image segmentation and nuclei detection”, Lecture Notes in Computer Science (ACIVS), Vol. 5259, pp. 903-914, 2008. 

*I. Ersoy, K. Palaniappan, “Multi-feature contour evolution for automatic live cell segmentation in time lapse imagery”, 30th IEEE Int. Conf. Engineering in Medicine and Biology (EMBC), pp. 371-374, 2008.

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