Es Cells Identification In Phase Contrast And Fluorescents Images Based On Level Set And Watershed Segmentation

862 words - 4 pages

The number of research groups and projects using human stem cells has increased largely in the last 5 years. Human embryonic stem-cell research is not only ethical; it is an essential field in biomedical research which applicable for medical treatment. These ES cells are potential use to treat diseases effectively where there are currently no cures, such as: Parkinson’s disease and cancer, cell therapies, etc. Hence, ES cells identificationis very important to locateES cells state in Microscopic image. However, identification ES cells is a difficult task due to the ES cells growing and culture, where the cells are capable of self-renewal and remain undifferentiated for a long time, and can ...view middle of the document...

This approach can handle well topological change and works efficiently on a merging and splitting shapes.The main idea of this method is to delineatea contour as zero level set of higher dimensional function, called level set function and formulate the motion of the contour as the evolution of the level set function [10].
Caselles et al. [5] introduced the level set methods in-dependently for image processing and computer vision application and Malladi et al [6] presented active contour (or snake model) [7] for image segmentation.In last a decade, various level set methods have been improved and proposed to regularize the LSF during evolution and to eliminate the re-initialization procedure.
A new variation formulation level set method was proposed by Chunming Li, et al in 2005 [8]. It aimed to remove the need of re-initialization and to force LSF to be close to a signed function. Tenn Francis Chen [9] implemented a level set approach for Medical image based on active contour segmentation. It can handle topological change with no requirement about object shapes. In 2010, chunming Li, et al.[10] proposed level set level set evolution algorithm that can simultaneously move the zero level set while maintaining the signed distance profile throughout the entire evolution.Chunming Li, et al. named this level set formulation as a distance regularized level set evolution (DRLSE). This method completely eliminated re-initialization procedure and allows the use of larger time step which can reduce computation time and number of iterations.
Another well-known segmentation technique is watershed based segmentation. Nassir salam [11] proposed a watershed technique combine with edge detection techniques for image segmentation. Lamia JaafarBelaid and...

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