International Journal of Biomedical Science and Engineering
Volume 4, Issue 3, June 2016, Pages: 22-27
Received: Sep. 19, 2016;
Published: Sep. 27, 2016
Views 3849 Downloads 125
Bohua Feng, College of Medical Information Engineering, Guangdong Pharmaceutical University, Guangzhou, P. R. China
Liufen Peng, College of Medical Information Engineering, Guangdong Pharmaceutical University, Guangzhou, P. R. China
Microscope images analysis of erythrocyte (red blood cells, RBCs) was a widely used method for medical purpose. Usually manual measuring and analysis of the images were subject to time-consuming, errors and unstability of results. The images analysis method had been combined with computer image processing techniques in this research. A measuring and analysis system for microscope images(MIAS) of RBCs was developed, which could recognize RBCs in images and measure cells mophometric parameters. Normal human RBCs were compared with ones under high glucose. The results indicated RBCs sizes parameters such as areas, perimeters, major axis lengths, minor axis lengths, elongations, roundnesses and Feret diameters have difference between normal and high glucose conditions. RBCs normal disk shapes changed into acanthocyte and stomatocyte under higher glucose conditions. This fast and precise method for measuring RBCs morphometric parameters contributed to pathogenesis of diabetic nephropathy(DN) research.
Erythrocyte Morphological Characteristics Based on Microscope Images System, International Journal of Biomedical Science and Engineering.
Vol. 4, No. 3,
2016, pp. 22-27.
Stein P. D., Goldman J., Matta F. Yaekoub A. Y., Diabetes Mellitus and Risk of Venous Thromboembolism, American Journal of the Medical Sciences, 2009, 337 (4), 259-264
Fan X., Zhang J., Theves M., Strauch C., Nemet I., Liu X., Qian J., Giblin F. J. Monnier V.M., Mechanism of lysine oxidation in human lens crystallins during aging and in diabetes, Journal of Biological Chemistry, 2009, 284 (50), 34618-34627
Trachtman H., Futterweit S., Pine E., Mann J., Valderrama E., Chronic diabetic nephropathy: role of inducible nitric oxide synthase, Pediatric Nephrology, 2002, 17 (17), 20-29
Thuraisingham R. C., Nott C. A., Dodd S.M., Yaqoob M. M., Increased nitrotyrosine staining in kidneys from patients with diabetic nephropathy, Kidney international, 2000, 57 (5), 1968-1972
Yong J. G., Ruan P., Feng B. H., Shi M. L. Peng L. F., Study on the relevance of changes in red blood cell morphology and function of patients with diabetic nephropathy to the development of diabetes, Journal of Jinan University (Natural Science & Medicine Edition), 2013, 34 (6), 610-614
Jiang J., Fan D. N., Chen W., Xiong Z. H., Erythrocyte counting system based on blood micrograph, Medical Information, 2009, 22 (1), 8-10
Yao C. C., Huang Y. X., LI X. K., Ruan P., Effects of pH on structure and function of single living erythrocyte, Chinese Science Bulletin, 2003, 48 (13), 1342-1346
Gabir M. M., Hanson R. L., Dabelea D., Imperatore G., Roumain J., Bennett P. H., Knowler W. C., The 1997 American Diabetes Association and 1999 World Health Organization criteria for hyperglycemia in the diagnosis and prediction of diabetes, Diabetes Care, 2000, 23 (8), 1108-1112
Foundation N. K., K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification, Annals of Internal Medicine, 2003, 139 (2), 137-147
Wang J. C., Shi Z. W., The significance of urine red blood cell morphology analysis in the differential diagnosis on diabetic nephropathy and non diabetic nephropathy, Journal of Practical Medicine, 2015, 31 (1), 95-97
Li H., Edge detection technology of image processing, Agriculture & Technology, 2010, 30 (2), 163-165