Large scale tracking of stem cells using sparse coding and coupled graphs

Jacob Schack Vestergaard; Anders Lindbjerg Dahl; Peter Holm; Rasmus Larsen

Large scale tracking of stem cells using sparse coding and coupled graphs

Jacob Schack Vestergaard, Anders Lindbjerg Dahl, Peter Holm, Rasmus Larsen

Research output: Contribution to conference › Poster › Research › peer-review

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Abstract

Stem cell tracking is an inherently large scale problem. The challenge is to identify and track hundreds or thousands of cells over a time period of several weeks. This requires robust methods that can leverage the knowledge of specialists on the field. The tracking pipeline presented here consists of a dictionary learning method for segmentation of phase contrast microscopy images. Linking of the cells between two images is solved by a graph formulation of the tracking problem.

Original language	English
Publication date	2012
Number of pages	1
Publication status	Published - 2012
Event	International Computer Vision Summer School (ICVSS 2012) - Sicily, Italy Duration: 15 Jul 2012 → 21 Jul 2012 http://svg.dmi.unict.it/icvss2012/

Seminar

Seminar	International Computer Vision Summer School (ICVSS 2012)
Country	Italy
City	Sicily
Period	15/07/2012 → 21/07/2012
Internet address	http://svg.dmi.unict.it/icvss2012/

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Poster, summerschoolFinal published version, 1.24 MB

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abstract = "Stem cell tracking is an inherently large scale problem. The challenge is to identify and track hundreds or thousands of cells over a time period of several weeks. This requires robust methods that can leverage the knowledge of specialists on the field. The tracking pipeline presented here consists of a dictionary learning method for segmentation of phase contrast microscopy images. Linking of the cells between two images is solved by a graph formulation of the tracking problem.",

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T1 - Large scale tracking of stem cells using sparse coding and coupled graphs

AU - Vestergaard, Jacob Schack

AU - Dahl, Anders Lindbjerg

AU - Holm, Peter

AU - Larsen, Rasmus

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AB - Stem cell tracking is an inherently large scale problem. The challenge is to identify and track hundreds or thousands of cells over a time period of several weeks. This requires robust methods that can leverage the knowledge of specialists on the field. The tracking pipeline presented here consists of a dictionary learning method for segmentation of phase contrast microscopy images. Linking of the cells between two images is solved by a graph formulation of the tracking problem.

M3 - Poster

T2 - International Computer Vision Summer School (ICVSS 2012)

Y2 - 15 July 2012 through 21 July 2012

ER -