Scientific and Technical Journal


ISSN Print 2221-3937
ISSN Online 2221-3805
Segmentation of dense tissue and lumen of human artery on ultrasound image is one of the tasks of each system that facilitates an extent assessment of arteries atherosclerotic lesions by ultrasound scan. The system which allows to segment ultrasound images of the carotid arteries was proposed in this paper. The system is based on two genetic algorithms (GA). GA was proposed for automatization of construction of ultrasound segmentation methods. The genetic algorithm find different solutions for predetermined processing result. Effectiveness of construction methods for image processing algorithm depends on the characteristics of images. Parallel genetic algorithm is used to find dependences between values of texture parameters of images and processing techniques. Ultrasound image processing system which is based on the above-described genetic algorithms allows to improve quality and speed of determining stage of atherosclerotic disease.
1. Mitrea D., Nedevschi S., Lupsor M., and Badea R., (2006), Exploring Texture-Based Pa-rameters for Noninvasive Detection of Diffuse Liver Diseases and Liver Cancer from Ultra-sound Images, Proc. of the 8th WSEAS Int. Conf. on Mathematical Methods and Computa-tional Techniques in Electrical Engineering, Bucharest, and October 16-17, 2006.
2. Loizou C., PhD Thesis, (2005), Ultra-sound Image Analysis of The Carotid Arterya, Kingston University London, UK.
3. Loizou C., (2008), Despeckle Filtering Algorithims and Software for Ultrasound Imag-ingm, Constantinos Pattichis, Costas Pattichis, A Publication in the Morgan & Claypool Publish-ers Series.
4. Lee J.S., (1980), Digital Image En-hancement and Noise Filtering by use of Local Statistics, IEEE Transactions on Pattern Analy-sis and Machine Intelligence, PAMI-2, pp. 165 – 168.
5. Lin Y., PhD Thesis, (2003), Feature Syn-thesis and Analysis by Evolutionary Computa-tion for Object Detection and Recognition, Uni-versity of California, Riverside.
6. Santos A.M.F., R. M. dos Santos, Castro P.M.A.C., Azevedo E., Sousa L., and Tavares J.M.R.S., (2013), A Novel Automatic Algorithm for the Segmentation of the Lumen of the Ca-rotid Artery in Ultrasound B-mode Images, Ex-pert Systems with Applications 40:16. – 6570-6579, Online Publication Date: 1-Nov-2013.
7. Molinari F., Acharya U.R., Zeng G., Meiburger K.M., and Suri J.S., (2011), Com-pletely Automated Robust edge Snapper for Ca-rotid Ultrasound IMT Measurement on a Multi-institutional Database of 300 images, Medical & Biological Engineering & Computing 49:8, 935-945, Online publication date: 1-Aug-2011.
8. Stoitsis J., Golemati S., and Nikita K.S., (2006), A Modular Software System to Assist Interpretation of Medical Images – Application to Vascular Ultrasound Images, IEEE Transac-tions On Instrumentation And Measurement, Vol. 55, No. 6, December, 2006.
9. Suri J.S., Yuan C., Wilson D.L., and Laxminarayan S., (2005), Plaque Imaging: Pixel to Molecular Level, Volume 113 of Studies in Health Technology and Informatics, May 2005, 488 p.
10. Weszka J.S.A., Dyer C.R., Rosenfeld A., (1976), Comparative Study of Texture Measures for Terrain Classification, IEEE Transactions on Systems, Man, And Cybernet-ics. – Vol. SMC-6, No. 4, April, 1976.
11. Yu-Hsiang Wu, Jhu-Yun Huang, Shyi-Chyi Cheng, Chen-Kuei Yang, and Chih-Lang, Lin, (2011), Evolutionary Feature Construction for Ultrasound Image Processing and Its Appli-cation to Automatic Liver Disease Diagnosis, International Conference on Complex, Intelli-gent, and Software Intensive Systems.
12..Belikova T., and Skobtsov V., (2011), Evolutsionnyiy poisk effectivnyh posle-dovatel’nostey fil’trov v zadache binarizatsii UZ izobrajeniy [Evolutionary Search for Effective Sequences of Filters in the Problem of Ultrasonic Images Binarization], Transactions of IAMM of NAS, Ukraine, Vol 23, pp. 21 – 34 (In Russian).
13. Belikova T., and Skobtsov V., Ge-neticheskiy algoritm v zadache filtratsii UZ izobrajeniy i analiz ego modoficatsiy, [Analysis of Genetic Algorithm Modications in the Problem of Filtering Ultrasound Images], (2012), Journal of Kherson National Technical University, Vol. 1(44), pp. 331 – 338 (In Rus-sian).
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