A Urinary Sediment Segmentation Algorithm of Cast and Epithelial Cells

Yan Hai Wu; Meng Kang

doi:10.4028/www.scientific.net/AMM.457-458.1046

Paper Titles

Robust Visual Tracking Using Particle Filtering on SL(3) Group
p.1028

Gaussian Noised Single-Image Super Resolution Reconstruction
p.1032

The Simulated Annealing Algorithm Based on Multi-Populations Application of TSP
p.1037

Design and Realization of a Certain Type of Radio RF Circuit Board Detecting and Teaching Platform
p.1042

A Urinary Sediment Segmentation Algorithm of Cast and Epithelial Cells
p.1046

Research on Target Tracking Algorithm Based on Particle Filter and Mean-Shift
p.1050

The Design of Car Taillight Controller Based on VHDL
p.1054

Calculation of Angular Variation of Spacecraft Assembly Considering Measurement Uncertainty
p.1058

A Modified Version of the K-Means Algorithm Based on the Shape Similarity Distance
p.1064

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 457-458A Urinary Sediment Segmentation Algorithm of Cast...

A Urinary Sediment Segmentation Algorithm of Cast and Epithelial Cells

Abstract:

Based on cast and epithelial cells to segment difficultly in urinary sediment, this paper propose one modified segmentation algorithm that is combining Sobel edge detection with edge enhancement algorithm, and using the fusion technology to get the whole binary results. Using cast and epithelial having great area is to remove small area impurity. Last after morphological operation can deserve a good split binary image. Experimental results show that the algorithm performs faster, complete binary cells and higher precision than segmentation algorithm from now on. The algorithm is not only suitable for cast and other large cells, but also satisfied for red and white cells, crystallize, sperm in urinary sediment.

You might also be interested in these eBooks

Frontiers of Mechanical Engineering and Materials Engineering II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 457-458)

Pages:

1046-1049

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.457-458.1046

Citation:

Cite this paper

Online since:

October 2013

Authors:

Yan Hai Wu, Meng Kang

Keywords:

Edge Enhancement, High Precision, Morphological Operation, Small Area, Sobel Edge Detection

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] WANG Jin-tao, LIU Wen-yao, LU Shou. Application of watershed algorithm to cell image segmentation [J]. Journal of Southwest Jiao tong University, 2002, 37 (3): 2272231.

Google Scholar

[2] ZHANG Jun-feng, JING Wei-na. Infrared Image Segmentation Based on Type-2Entropy Fuzzy Clustering UsingL1Metric [J] ．Microelectronics & Computer, 2010, 27(1) ：49-52.

Google Scholar

[3] Yong-Ming Li, Xiao-Ping Zing. A new strategy for urinary sediment segmentation based on wavelet, morphology and combination method. Computer methods and programs in biomedicine, 84 (2006) ：162-173.

DOI: 10.1016/j.cmpb.2006.07.010

Google Scholar

[4] CAO Yang, SU Li-na, SHEN Qi, QU Xiao-feng. Design and Realization of Improved Sobel Edge Detection Algorithm Based on FPGA [J]. Microelectronics & Computer, 2012, 29(10) ：124-127.

Google Scholar

[5] TANG Yan-ping, ZHANG Can-long. Urine sediment extraction base on morphology and active con tour model[J]. Journal of Guilin University of Electronic Technology，2007，27（6）：482-486.

Google Scholar