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Journal Biomedical Radioelectronics №1 for 2015 г.
Article in number:
Segmentation of scintigraphic images of kidneys with <sup>99m</sup>Tc-DMSA
Authors:
N.А. Nikolov - Ph.D. (Eng.), Associate Professor, Department of Physical and Biomedical Electronics, National Technical University of Ukraine «Kiev Polytechnic Institute», Kiev, Ukraine; Associate Professor, Department of Telecommunication Technologiesof, State University of Telecommunications, Kiev, Ukraine
D.А. Supruniuk - Post-graduate Student, Department of Physical and Biomedical Electronics, National Technical University of Ukraine «Kiev politechical institute», Kiev, Ukraine A.L. Kaminskaya - Ph.D.(Med.), Head of Department of nuclear medicine, Kiev Clinical Hospital № 14, Kiev, Ukraine
V.B. Chizhevsky - Student, Department of Physical and Biomedical Electronics, National technical university of Ukraine «Kiev politechical institute», Kiev, Ukraine
Abstract:
One of the most informative and perspective methods of studies of functional state of kidney in children and adult is nephroscintigraphic with 99mTc-DMSA (dimercaptosuccinic acid). Special importance of scintigraphy with 99mTc-DMSA acquires at monitoring studies, evaluating the dynamics of kidney disease and the effectiveness of therapy. Primarily in such studies the attention pays to the appearance of new focuses with hypofixation of RFC, which interpreted as area of renal tissue sclerosis. For an objective assessment of these processes requires the evaluation of the specific percent of RFC inclusion in abnormal areas, evaluation forms of focuses and their quantity. The fundamental technical problem for solving these tasks is development of image segmentation algorithm. The purpose of this work is developing universal segmentation methods of scintigraphic images of kidney with 99mTc-ДМСА with considering areas of drug hypofixation as fuzzy aggregate. Since scintigraphic images are characterized by low-resolution, high noise levels and focus of drugs hypo fixation have fuzzy and rough contours, was proposed to estimate renal parenchyma lesion area as a fuzzy aggregate. For such solution was developed three estimate algorithms for the upper and lower limits, as well as the «average» values of the lesion area. The estimation for upper limit of kidney lesions was proposed to perform by comparing real image of kidney and idealized model; lower limit was defined by searching local minimums of spatial distribution of drug in parenchyma; "average" values was defined as contour changes of kidney at percentage variation of cutoff tissue background.
Pages: 3-11
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