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Proceedings Paper

Neurosphere segmentation in brightfield images
Author(s): Jierong Cheng; Wei Xiong; Shue Ching Chia; Joo Hwee Lim; Shvetha Sankaran; Sohail Ahmed
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Paper Abstract

The challenge of segmenting neurospheres (NSPs) from brightfield images includes uneven background illumination (vignetting), low contrast and shadow-casting appearance near the well wall. We propose a pipeline for neurosphere segmentation in brightfield images, focusing on shadow-casting removal. Firstly, we remove vignetting by creating a synthetic blank field image from a set of brightfield images of the whole well. Then, radial line integration is proposed to remove the shadow-casting and therefore facilitate automatic segmentation. Furthermore, a weighted bi-directional decay function is introduced to prevent undesired gradient effect of line integration on NSPs without shadow-casting. Afterward, multiscale Laplacian of Gaussian (LoG) and localized region-based level set are used to detect the NSP boundaries. Experimental results show that our proposed radial line integration method (RLI) achieves higher detection accuracy over existing methods in terms of precision, recall and F-score with less computational time.

Paper Details

Date Published: 21 March 2014
PDF: 7 pages
Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90344D (21 March 2014); doi: 10.1117/12.2043365
Show Author Affiliations
Jierong Cheng, Institute for Infocomm Research (Singapore)
Wei Xiong, Institute for Infocomm Research (Singapore)
Shue Ching Chia, Institute for Infocomm Research (Singapore)
Joo Hwee Lim, Institute for Infocomm Research (Singapore)
Shvetha Sankaran, Institute of Medical Biology (Singapore)
Sohail Ahmed, Institute of Medical Biology (Singapore)


Published in SPIE Proceedings Vol. 9034:
Medical Imaging 2014: Image Processing
Sebastien Ourselin; Martin A. Styner, Editor(s)

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