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Neurosphere fate prediction: An analysis-synthesis approach for feature extraction

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6 Author(s)
Stéphane U. Rigaud ; Image & Pervasive Access Lab., Singapore, Singapore ; Nicolas Loménie ; Shvetha Sankaran ; Sohail Ahmed
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The study of stem cells is one of the current most important biomedical research field. Understanding their development could allow multiple applications in regenerative medicine. For this purpose, we need automated methods for the segmentation and the modeling of neural stem cell development process into a neurosphere colony from phase contrast microscopy. We use such methods to extract relevant structural and textural features like cell division dynamism and cell behavior patterns for biological interpretation. The combination of phase contrast imaging, high fragility and complex evolution of neural stem cells pose many challenges in image processing and image analysis. This study introduces an on-line analysis method for the modeling of neurosphere evolution during the first three days of their development. From the corresponding time-lapse sequences, we extract information from the neurosphere using a combination of fast level set and curve detection for segmenting the cells. Then, based on prior biological knowledge, we generate possible and optimal 3-dimensional configuration using registration and evolutionary optimisation algorithm.

Published in:

The 2012 International Joint Conference on Neural Networks (IJCNN)

Date of Conference:

10-15 June 2012