Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/36148
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
Source: 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.
URI: http://scholarbank.nus.edu.sg/handle/10635/36148
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
TU_YJ MSc thesis.pdf1.88 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

164
checked on Dec 2, 2017

Download(s)

452
checked on Dec 2, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.