Title
Microscopic Cell Detection Based on Multiple Cell Image Segmentations and Fusion Algorithms
Abstract
Automatic cell segmentation in phase contrast microscopy images play a very important role in the study the behavior of lymphocytes, such as cell motility, cell deformation, and cell population dynamics etc. In this paper, we have developed a set of algorithms for the microscopy image cell segmentation, in which three pairs of edge detection (Sobel, Prewitt and Laplace) based cell segmentation algorithms are developed in parallel to increase the probability of cell detection. Then, an hierarchical model is proposed and used in decision fusion that combine the three pair of detection results to increase the probability of final cell detection. After that, a false removal algorithm is proposed to remove false detections that may occur in the fusion process. The distance and watershed transforms have also been used to separate the connected cells. Experimental results have proved that these algorithms are pretty robust to variable microscopy image data, and variable cell densities, and with the proposed fusion and false removal algorithms, the cell detection rate has increased significantly to above 97% with the false detection rate about 7%.
Year
DOI
Venue
2009
10.1109/BMEI.2009.5305006
Tianjin
Keywords
Field
DocType
cellular biophysics,edge detection,image fusion,image segmentation,medical image processing,decision fusion,distance transform,edge detection,false removal algorithm,hierarchical model,microscopic cell detection,multiple cell image fusion algorithm,multiple cell image segmentation algorithm,watershed transform
Population,Image fusion,Computer science,Edge detection,Image segmentation,Sobel operator,Distance transform,Artificial intelligence,Hierarchical database model,Computer vision,Pattern recognition,Algorithm,Prewitt operator
Conference
ISSN
ISBN
Citations 
1948-2914
978-1-4244-4134-1
4
PageRank 
References 
Authors
0.42
3
3
Name
Order
Citations
PageRank
Eric Dahai Cheng11139.69
Subhash Challa225224.96
Rajib Chakravorty3447.52