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Title: Automatic cell model generation from integrated cell image database
Authors: TU YAJING
Keywords: Cell Image Segmentation, Cell tracking, DIC, Watershed, Active Contour, Image Pre-processing
Issue Date: 15-Jun-2012
Citation: TU YAJING (2012-06-15). Automatic cell model generation from integrated cell image database. ScholarBank@NUS Repository.
Abstract: Image segmentation is a complex problem with many practical applications. In particular cell image segmentation and cell tracking through a series of images has the potential to increase the throughput of cell experiments.. This paper addresses the problem with DIC cell images. In this paper, local contrast enhancement and N-L means image denoising are proposed for image pre-processing which improves the quality of the image to a great extend. After that several image segmentation methods are applied. The first solution is based on a seeded watershed segmentation technique, and the second one is based on active contours using level set function. The algorithm is further extended to cell tracking problems. The active contours produces good results for images with single cell, and for cell clustering the combination of active contours and seeded watershed produced good results.
Appears in Collections:Master's Theses (Open)

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