Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma

This work is aimed at studying the possibilities of Mueller-matrix diagnostics applied to optically anisotropic birefringent polycrystalline networks inherent to amino acids in human blood plasma. Determined here are interrelations between statistical moments of the first to fourth orders as well as...

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Date:2011
Main Authors: Ushenko, Yu.A., Olar, O.I., Dubolazov, A.V., Balanetskaya, V.O., Unguryan, V.P., Zabolotna, N.I., Oleinichenko, B.P.
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Language:English
Published: Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України 2011
Series:Semiconductor Physics Quantum Electronics & Optoelectronics
Online Access:https://nasplib.isofts.kiev.ua/handle/123456789/117650
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Cite this:Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma/ Yu.A. Ushenko, O.I. Olar, A.V. Dubolazov, V.O. Balanetskaya, V.P. Unguryan, N.I. Zabolotna, B.P. Oleinichenko // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2011. — Т. 14, № 1. — С. 98-105. — Бібліогр.: 39 назв. — англ.

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spelling nasplib_isofts_kiev_ua-123456789-1176502025-06-03T16:28:46Z Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma Ushenko, Yu.A. Olar, O.I. Dubolazov, A.V. Balanetskaya, V.O. Unguryan, V.P. Zabolotna, N.I. Oleinichenko, B.P. This work is aimed at studying the possibilities of Mueller-matrix diagnostics applied to optically anisotropic birefringent polycrystalline networks inherent to amino acids in human blood plasma. Determined here are interrelations between statistical moments of the first to fourth orders as well as fractal dimensionalities that characterize coordinate distributions of blood plasma Mueller-matrix elements and the physiological state of a human organism. 2011 Article Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma/ Yu.A. Ushenko, O.I. Olar, A.V. Dubolazov, V.O. Balanetskaya, V.P. Unguryan, N.I. Zabolotna, B.P. Oleinichenko // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2011. — Т. 14, № 1. — С. 98-105. — Бібліогр.: 39 назв. — англ. 1560-8034 PACS 78.20.Fm, 87.64.-t https://nasplib.isofts.kiev.ua/handle/123456789/117650 en Semiconductor Physics Quantum Electronics & Optoelectronics application/pdf Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
institution Digital Library of Periodicals of National Academy of Sciences of Ukraine
collection DSpace DC
language English
description This work is aimed at studying the possibilities of Mueller-matrix diagnostics applied to optically anisotropic birefringent polycrystalline networks inherent to amino acids in human blood plasma. Determined here are interrelations between statistical moments of the first to fourth orders as well as fractal dimensionalities that characterize coordinate distributions of blood plasma Mueller-matrix elements and the physiological state of a human organism.
format Article
author Ushenko, Yu.A.
Olar, O.I.
Dubolazov, A.V.
Balanetskaya, V.O.
Unguryan, V.P.
Zabolotna, N.I.
Oleinichenko, B.P.
spellingShingle Ushenko, Yu.A.
Olar, O.I.
Dubolazov, A.V.
Balanetskaya, V.O.
Unguryan, V.P.
Zabolotna, N.I.
Oleinichenko, B.P.
Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma
Semiconductor Physics Quantum Electronics & Optoelectronics
author_facet Ushenko, Yu.A.
Olar, O.I.
Dubolazov, A.V.
Balanetskaya, V.O.
Unguryan, V.P.
Zabolotna, N.I.
Oleinichenko, B.P.
author_sort Ushenko, Yu.A.
title Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma
title_short Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma
title_full Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma
title_fullStr Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma
title_full_unstemmed Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma
title_sort mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma
publisher Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
publishDate 2011
url https://nasplib.isofts.kiev.ua/handle/123456789/117650
citation_txt Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma/ Yu.A. Ushenko, O.I. Olar, A.V. Dubolazov, V.O. Balanetskaya, V.P. Unguryan, N.I. Zabolotna, B.P. Oleinichenko // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2011. — Т. 14, № 1. — С. 98-105. — Бібліогр.: 39 назв. — англ.
series Semiconductor Physics Quantum Electronics & Optoelectronics
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fulltext Semiconductor Physics, Quantum Electronics & Optoelectronics, 2011. V. 14, N 1. P. 98-105. PACS 78.20.Fm, 87.64.-t Mueller-matrix diagnostics of optical properties inherent to polycrystalline networks of human blood plasma Yu.A. Ushenko1, O.I. Olar2, A.V. Dubolazov3, V.O. Balanetskaya3, V.P. Unguryan4, N.I. Zabolotna5, B.P. Oleinichenko6 1Chernivtsi National University, Department for Correlation Optics, 2, Kotsyubinsky vul., 58012 Chernivtsi, Ukraine, yuriyu@gmail.com 2Bukovina State Medical University, Department of Biophysics and Medical Informatics, 2, Teatralnaya Sq., 58012 Chernivtsi, Ukraine. 3Chernivtsi National University, Department for Optics and Spectroscopy, 2, Kotsyubinsky vul., 58012 Chernivtsi, Ukraine. 4Bukovina State Medical University, Department for Oncology, 2, Teatralnaya ploshchad, 58012 Chernivtsi, Ukraine. 5Vinnytsa National Technical University, Department for Laser and Optoelectronic Technique, 95, Khmelnitskoye shosse, 21021 Vinnytsa, Ukraine. 6Medical Center “Medivin”, 95, Khmelnitskoye shosse, 21021 Vinnytsa, Ukraine. Abstract. This work is aimed at studying the possibilities of Mueller-matrix diagnostics applied to optically anisotropic birefringent polycrystalline networks inherent to amino acids in human blood plasma. Determined here are interrelations between statistical moments of the first to fourth orders as well as fractal dimensionalities that characterize coordinate distributions of blood plasma Mueller-matrix elements and the physiological state of a human organism. Keywords: polarization, Mueller matrix, optical anisotropy, birefringence, statistical moments, fractal, blood plasma. Manuscript received 07.10.10; accepted for publication 02.12.10; published online 28.02.11. 1. Introduction Among the diversity of directions for optical diagnostics of the structure typical for phase-inhomogeneous layers, Mueller-matrix polarimetry of optical anisotropy observed in human biological tissues (BT) is rather developed [1 – 39]. The main result of this diagnostics lies in determination of the set of interrelations between statistical as well as fractal parameters of coordinate distributions for matrix elements and an optical- geometrical structure of BT birefringent component [1 – 6, 9, 11, 12, 14, 38]. It serves as a basis to develop the methods for early diagnostics of pathological changes in skin derma, epithelial and connective tissue of woman reproductive organs etc. [11, 14, 21 – 27, 35, 36]. At the same time, one of the lacks of this optical- medical technology is the traumatic biopsy operation. Therefore, it seems topical to spread Mueller-matrix diagnostics over a wide and accessible circle of biological objects. These are various biological liquids, namely: blood, urine, bile, joint fluid, etc. Our work is aimed at development of the Mueller matrix method for diagnostics of optically anisotropic structure typical for blood plasma proteins, as it is topical to determine statistical and fractal criteria of transformations in amino acid polycrystalline networks, which are caused by pathological changes in human organism. 2. Mueller-matrix modeling the polarization properties of polycrystalline protein networks in blood plasma Our analysis of optical properties inherent to polycrystalline protein networks created by blood plasma amino acids is based on the following model [5, 6, 15, 23, 28, 29]: • blood plasma is considered as a two-component isotropic-anisotropic structure; • а optically anisotropic component is represented by the protein fraction consisting of optically single-axis birefringent crystals of amino acids albumin and globulin; • polarization properties of these biological crystals are characterized with the Mueller matrix © 2011, V. Lashkaryov Institute of Semiconductor Physics, National Academy of Sciences of Ukraine 98 Semiconductor Physics, Quantum Electronics & Optoelectronics, 2011. V. 14, N 1. P. 98-105. { } 444342 343332 242322 0 0 0 0001 zzz zzz zzz z u = , (1) where ( ) ( ) ⎪ ⎪ ⎪ ⎪ ⎩ ⎪ ⎪ ⎪ ⎪ ⎨ ⎧ δ= δρ±= δρ±= δρ+ρ= δ−ρρ= δρ+ρ= = .cos ,sin2sin ,sin2cos ,cos2cos2sin ,cos12sin2cos ,cos2sin2cos 44 42,24 43,34 22 33 32,23 22 22 z z z z z z z uik (2) Here, is the direction of the optical axis; ρ ndΔλ π=δ 2 – phase shift between orthogonal components of the amplitude, - wavelength, - geometric distance, - index of birefringence; λ d nΔ • Mueller matrix elements for the planar network layer (N) of crystalline amino acids are determined by superposition of partial matrix operators (relation (1)) ikR ( )∑ = = N u uikik zR 1 , (3) • Mueller matrix of multilayer ( ) polycrystalline network is determined with the product of partial matrix operators (relation (3)) n { } { } { } { } { }121... RRRRP nn −= , (4) To simplify (without any losses of fullness) our consideration, let us use the approximation of two-layer polycrystalline protein network { } { } { } { }{ }XYRRP ≡= 12 . (5) In a detailed look, the expression (5) can be written as ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎩ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎨ ⎧ ++= ++= ++= ++= ++= ++= ++= ++= ++= = . , , , , , , , , 44443443244244 42443243224242 44243423242224 43443343234243 44343433243234 43343333233233 42343233223232 43243323232223 42243223222222 xyxyxyp xyxyxyp xyxyxyp xyxyxyp xyxyxyp xyxyxyp xyxyxyp xyxyxyp xyxyxyp pik (6) Our analysis of relations (1), (2), (5) and (6) shows that the exact solution of the inverse problem – revealing the changes in the structure of polycrystalline protein networks in separate layers by using available information on matrix elements , - is incorrect from the mathematical viewpoint and ambiguous from the physical one. ikp Thus, it seems topical to use the statistical and fractal approaches to the analysis of distributions inherent to Mueller matrix elements in optically anisotropic polycrystalline protein component of blood plasma. 3. Statistical and fractal analyses of Mueller-matrix images for networks of biological crystals Coordinate distributions of Mueller matrix elements in blood plasma were estimated within the frameworks of statistical and fractal approaches. ikp The statistical moments of the first to fourth orders that characterize the distributions were calculated using the following relations [5, 8] ),( yxpik ;1 1 1 j N j ikp Q M ∑ = = ;)(1 1 2 2 ∑ = = N j jikp Q M ∑ = = N j jikp QM M 1 3 3 2 3 ;)(11 ∑ = = N j jikp QM M 1 4 2 2 4 )(11 , (7) where is the number of pixels in CCD camera. !Q The fractal analysis of distributions was made by finding the logarithmic dependences ),( yxpik ( ) )log(log 1−− dpJ ik for the power spectra ( )ikpJ [5, 15] ( ) ∫ +∞ ∞− νπν= dppJ ikik 2cos , (8) where are spatial frequencies determined by the range of changing the sizes of structural elements in the polycrystalline network. 1−=ν d d The dependences were approximated using the least-squares method to the curves ( ) )log(log 1−− dpJ ik ( )ηΦ , straight parts of which allow determining the slope angles η and respective fractal dimensionalities [5, 15] η−= tgD 3 . (9) Classification of coordinate distributions was performed in accord with the following criteria: ),( yxpik • are fractal or self-similar, if η = const within the limits of 2 or 3 decades for changing the geometric sizes ; ),( yxpik d • are multifractal when several constant slope angles ),( yxpik const;...2;1 =η =j are available: • are statistical or random, if ),( yxpik const≠η over all the interval for changing . d © 2011, V. Lashkaryov Institute of Semiconductor Physics, National Academy of Sciences of Ukraine 99 Semiconductor Physics, Quantum Electronics & Optoelectronics, 2011. V. 14, N 1. P. 98-105. 4. Scheme and method of measurements Shown in Fig. 1 is the traditional optical scheme of the polarimeter used for measuring the coordinate distributions of Mueller matrix elements or Mueller- matrix images (MMI) [5]. Illumination of blood plasma samples was made with a parallel ( ) weakly intense (W = 5.0 mW) beam of He-Ne laser (λ = 0.6328 µm). The polarization illuminator consists of quarter-wave plates 3, 5 and the polarizer 4, which provides formation of the laser beam with an arbitrary azimuth and ellipticity of polarization. mμ×= 3102ЁЄ The studied human blood plasma sample was sequentially probed with the laser beam possessing the following types of polarization: linear with the azimuths 0°, 90°, +45° and right circular (⊗). Using the micro- objective 7, the polarization images were projected onto the plane of the sensitive area ( pixels) of CCD camera 10. The analysis of images of human blood plasma was made using the analyzer 9 and quarter-wave plate 8. 600800×=× nm Our calculation of Mueller matrix elements for the studied samples was performed in accord with the following algorithm [5] ; ; );(5,0 );(5,0 11114 11 45 113 90 1 0 112 90 1 0 111 pSp pSp SSp SSp −= −= −= += ⊗ (10) ; ; );(5,0 );(5,0 21224 21 45 223 90 2 0 222 90 2 0 221 pSp pSp SSp SSp −= −= −= += ⊗ ; ; );(5,0 );(5,0 31334 31 45 333 90 3 0 332 90 3 0 331 pSp pSp SSp SSp −= −= −= += ⊗ . ; );(5,0 );(5,0 41444 41 45 443 90 4 0 442 90 4 0 441 pSp pSp SSp SSp −= −= −= += ⊗ Here, are the Stokes vector parameters. ⊕ = ;90;45;0 4;3;2;1jS 5. Brief characterization of the investigated objects As objects of investigation, we chose the samples of blood plasma for two groups of patients: healthy woman and that with cancer of mammary gland (Figs 1c and 1d). The respective polycrystalline networks for blood plasma amino acids are illustrated with a set of laser images obtained in co-axial ( ) and crossed ( ) transmission planes of the polarizer 4 and analyzer 9 (Fig. 1). 00=Θ 090=Θ Our comparative analysis of these laser images found out different coordinate structures for albumin and globulin networks. In the optically anisotropic component of healthy woman blood plasma, one can observe albumin crystals spatially-ordered along several directions (Figs 1a and 1b). While blood plasma of the patient with the oncologic process contains mainly globulin crystals disordered as to directions of optical axes (Figs 1c and 1d). 6. Diagnostic possibilities for statistical and fractal analyses of Mueller-matrix images obtained for human blood plasma The subject of our statistical and fractal analyses was three types of Mueller-matrix images ( nmpik )× for human blood plasma. The first one is the coordinate distributions of diagonal elements in the Mueller matrix ( )nmp ×33;22 , which characterize the degree of transformation of the laser wave polarization azimuth by amino acid crystals, optical axes of which are oriented along two mutually orthogonal directions (00 900 ↔=ρ ( )nmp ×22 ) and © 2011, V. Lashkaryov Institute of Semiconductor Physics, National Academy of Sciences of Ukraine Fig. 1. Optical scheme of the polarimeter: 1 – He-Ne laser; 2 – collimator; 3 – stationary quarter-wave plate; 5, 8 – mechanically movable quarter-wave plates; 4, 9 – polarizer and analyzer, respectively; 6 – studied object; 7 – micro- objective; 10 – CCD camera; 11 – personal computer. See explanation in the text. 100 Semiconductor Physics, Quantum Electronics & Optoelectronics, 2011. V. 14, N 1. P. 98-105. © 2011, V. Lashkaryov Institute of Semiconductor Physics, National Academy of Sciences of Ukraine )00 13545 ↔=ρ ( ), respectively. In this sense, these matrix elements will be named as the “orientational” ones. ( nmp ×33 The second type is coordinate distributions for the diagonal matrix element ( )nmp ×44 , the value of which is determined by phase shifts between orthogonal components for the laser wave amplitude that artise as a consequence of birefruingence caused by crystalline amino acids. In this sense, this element of the Mueller matrix will be named as “phase” one. The third type is coordinate distributions of off- diagonal elements in the Mueller matrix , which characterize mechanisms of mutual transformations of linear polarization into a elliptic one, and vice versa. These matrix elements will be named as the “orientational-phase” ones. ( nmp ×34;24;23 ) ) Shown in Fig. 2 are the results of investigations of the following MMI structures observed for blood plasma of the healthy patient: coordinate ( ( nmpik × , left column), statistical (histograms and statistical moments of the first and fourth orders , central column) as well as fractal (logarithmic dependences , right column). ( ikph ) ) ) nmp ×33;22 4;3;2;1=jM ( ) )log(log 1−− dpJ ik Our analysis of the obtained data enabled us to reveal: “Orientational” matrix elements ( )nmp ×33;22 Histograms and are characterized with pronounced main extremes. Formation of these extremes may be related with superposition of matrix elements ) (relations (3)), values of which are determined by albumin crystals ordered relatively two or three separated directions of optical axes (relations (2), Figs 1a and 1b). ( 22ph ( 33ph ( The most pronounced differentiation of the coordinate distributions for matrix elements ( )nmp ×22 and of the polycrystalline network in blood plasma can be realized using the statistical moments of the third and fourth orders. Differences between the values ( nmp ×33 ) ( )33;223 pM and ( )33;224 pM in these distributions can reach 4 and 2.5 times, respectively (Fig. 2, central column). Our analysis of the dependences ; ( ) )log(log 1 22 −− dpJ ( ) )log(log 1 33 −− dpJ allowed us to reveal stability in the values of slope angles η within the range of changes in geometric sizes of amino acid crystals from 50 up to 1000 µm (Fig. 2, right column). This result is indicative of the fractal structure inherent to the distributions of , which can be related with an order of optical axis directions for albumin crystals. By contrast, disorder in globulin crystal orientations within the range of lower geometric sizes (d = 2…50 µm) causes randomness in coordinate distributions of d ( nmZ ×33;22 ) ρ ( )nmp ×33;22 . Quantitatively, this fact is expressed through the absence of any stable slope angle for the dependences ( ) ;loglog 1 22 −− dpJ ( ) 1 33 loglog −− dpJ . “Phase” matrix elements ( )nmp ×44 The histogram ( )44ph for the distribution of values inherent to the “phase” matrix element for blood plasma of healthy woman is characterized by a wide range of changes in values caused by variations of geometric sizes (d = 1…1000 µm) of albumin and globulin crystals (relation (2)). 44p The coordinate distribution of ( nmp )×44 is multifractal, since the curves approximating the logarithmic dependences are polygonal lines with several slope angles (Fig. 2, right column). ( )ηΦ ( ) 1 44 loglog −− dZJ η The found multifractality of the distribution corresponding to the “phase” matrix element ( )nmp ×44 of blood plasma is apparently caused by multiple changes ( ;...2;1;0,2 =π+δ=δ kk ) in phase shifts δ , which is related with different scales of geometric sizes inherent to albumin (50…1000 µm) and globulin (1…50 µm) crystals. “Orientational -phase” matrix elements ( )nmp ×34;24;23 The histograms ( )23ph , ( )24ph and for the distributions ( 34ph ) ( )nmp ×34;24;23 are practically “equiprobable”. Here, we do not take into account the main extreme ( ) 034;24;23 →ph , formation of which is caused by the influence of optically isotropic component in blood plasma. The wide range of changes in local extremes ( ) 034;24;23 ≠ph can be related with a simultaneous influence of both optical axis orientation and phase shift ρ δ (relations (2) and (3)) for local crystals in albumin-globulin blood plasma network on formation of the value of “orientational-phase” matrix elements. It was ascertained that differentiation of optical properties inherent to these networks can be efficiently performed using determination of the fourth order statistical moments for elements of MMI, because differences between values reach 3 times. ( nmp ×34;24;23 ) 4M Our analysis of the power spectra ( )34;24;23pJ found multifractality of distributions for matrix elements ( )nmp ×34;24;23 corresponding to healthy woman blood plasma. It was ascertained that elements ( nmp ×34;24;23 ) 101 Semiconductor Physics, Quantum Electronics & Optoelectronics, 2011. V. 14, N 1. P. 98-105. Fig. 2. Statistical and fractal structure of blood plasma MMI for a healthy patient. in MMI are characterized with individual sets of fractal dimensionalities (Fig. 2, right column). Shown in Fig. 3 is the set of statistical ( ( )ikph ; ) and fractal ( ) parameters that characterize elements in MMI of polycrystalline networks of amino acids in blood plasma of the patient with mammary gland cancer. 4;3;2;1=jM ( ) qik FdpJ ;loglog 1−− ( nmpik × The analysis of MMI for the respective blood plasma samples found essential transformation of histograms ( )ikph . The histograms ( )22ph and are characterized with redistribution of extremes, which can be related with changes in orientations of optical axes ( 33ph ) ( )nm×ρ and phase shift values in the albumin- globulin network of blood plasma (Fig. 3, central column). From the biochemical viewpoint, this process is caused by growth of the globulin concentration in ( nm×δ ) ) © 2011, V. Lashkaryov Institute of Semiconductor Physics, National Academy of Sciences of Ukraine 102 Semiconductor Physics, Quantum Electronics & Optoelectronics, 2011. V. 14, N 1. P. 98-105. blood plasma. As a result, we deal with disordering the directions of optical axes inherent to globulin crystals and growth of their birefringence. Therefore, the range of changes in values of “orientational” matrix elements is expanded, and the main extremes33;22p ( )122 →ph , are “shifted” (relations (2), (3)). ( 133 →ph © 2011, V. Lashkaryov Institute of Semiconductor Physics, National Academy of Sciences of Ukraine ) Changes in birefringence of blood plasma polycrystalline network observed in the samples taken from patients with mammary gland cancer are also pronounced in formation of practically equiprobable distributions of “phase” and “orientational-phase” matrix elements. 44p 34;24;23p The analysis of the power spectra ( )ikpJ for pathologically changed blood plasma found the tendency to growth of the amount of fractal dimensionalities for coordinate distributions of “orientational” ( )nmp ×33;22 , “orientational-phase” and “phase” elements (Fig. 3, right column). ( nmp ×34;24;23 ) )( nmp ×44 With the aim to determine the quantitative Mueller- matrix statistical and fractal criteria for differentiation of polycrystalline protein networks of amino acids, we have investigated blood plasma samples taken from two groups of patients, namely: healthy ones (21 persons) and those sick of cancer (19 persons). Summarized in Table 1 are the statistical moments from the first to fourth orders that characterize coordinate distributions of “orientational” , “orientational-phase” and “phase” elements of the Mueller matrix corresponding to blood plasma of both groups. 33;22p 34;24;23p 44p Our comparative analysis of the values and ranges for changes of statistical parameters Mj found for blood plasma of healthy patients and those sick of cancer enabled us to reveal the following features: • asymmetry values for the distributions of “orientational” matrix elements 3M ( )nmp ×33;22 describing blood plasma of oncologically sick patients decrease by 1.4 to 5 and 1.8 to 7.5 times, respectively; • excess for the coordinate distribution of the “phase” element 4M ( )nmp ×44 corresponding to pathologically changed polycrystalline protein network of amino acids in blood plasma is 20-fold decreased; • decrease of the values inherent to statistical moments of the third and fourth orders in the coordinate distributions of “orientational-phase” elements in the Mueller matrix ( )nmp ×34;24;23 reaches 4.3 to 5 and 7 to 20 times, respectively. Table 1. Statistical moments for distributions of pik(m×n) pik M Norm Mammary gland j cancer M1 0.73 ± 0.087 0.7 4 2 ± 0.08 M2 0.06 ± 0.008 0.07 ± 0.009 M3 1.68 ± 0.23 0.31 ± 0.037 p22 M4 3.25 ± 0.44 0.47 ± 0.054 M1 0.76 ± 0.088 0.78 ± 0.084 M2 0.04 ± 0.006 0.06 ± 0.008 M3 0.43 ± 0.057 0.32 ± 0.039 p33 M4 2.42 ± 0.31 1.32 ± 0.18 M1 0.17 ± 0.022 0.32 ± 0.041 M2 0.12 ± 0.018 0.14 ± 0.018 M3 0.23 ± 0.033 0.28 ± 0.036 p44 M4 2.09 ± 0.27 0.11 ± 0.015 M1 0.19 ± 0.024 0.16 ± 0.021 M2 0.05 ± 0.007 0.03 ± 0.004 M3 0.87 ± 0.093 0.16 ± 0.022 p23 M4 7.27 ± 0.96 0.35 ± 0.045 M1 0.21 ± 0.028 0.17 ± 0.024 M2 0.06 ± 0.008 0.03 ± 0.005 M3 0.99 ± 0.11 0.13 ± 0.017 p24 M4 2.58 ± 0.32 2.72 ± 0.33 M1 0.15 ± 0.019 0.34 ± 0.042 M2 0.10 ± 0.012 0.11 ± 0.015 M3 0.96 ± 0.099 0.19 ± 0.025 p34 M4 2.34 ± 0.28 0.25 ± 0.029 hus, just the statistical moments of higher orders are t the values of fractal dime T he most sensitive to changes in optically isotropic structure of blood plasma. Table 2 illustrates nsionalities for ( )nmpik × elements in MMI of blood plasma in both g The comparative analy roups. sis of the obtained data indic ormation of fractal distributions for • hus, it can be contended that biochemical changes in th ates: • transf “orientational” moments into the multifractal ones; 15% to 25% growth of the value and amount of fractal dimensionalities qF for distributions of “orientational-phase” and “phase” elements. T e blood plasma structure are clearly pronounced in changes of statistical and fractal parameters characterizing the set of MMI elements ( )nmpik × and can be applied as new criteria for diagno man pathological states. stics of hu 103 Semiconductor Physics, Quantum Electronics & Optoelectronics, 2011. V. 14, N 1. P. 98-105. Table 2. Fractal dimensionalities for distributions of the Mueller matrix elements Zik Dq Norm Mammary gland cancer D1 2.12 ± 0.14 2.17 ± 0.18 D2 - 1.86 ± 0.15 Z22 D3 - 2.01 ± 0.21 D1 2.09 ± 0.12 2.14 ± 0.14 D2 - 1.94 ± 0.13 Z33 D3 - 2.03 ± 0.19 D1 1.98 ± 0.127 2.07 ± 0.21 D2 1.76 ± 0.19 1.83 ± 0.17 Z44 D3 - 2.31 ± 0.24 D1 2.07 ± 0.19 2.12 ± 0.18 D2 2.18 ± 0.13 2.27 ± 0.19 Z23 D3 - 1.83 ± 0.13 D1 1.83 ± 0.18 1.97 ± 0.21 D2 2.05 ± 0.26 2.11 ± 0.14 Z34 D3 - 1.81 ± 0.16 © 2011, V. Lashkaryov Institute of Semiconductor Physics, National Academy of Sciences of Ukraine References 1. de Boer J F and Milner T E 2002 Review of polarization sensitive optical coherence tomography and Stokes vector determination J. Biomed. Opt. 7 359-71 2. de Boer J F, Milner T E and Nelson J S 1998 Trends in Optics and Photonics (TOPS): Advances in Optical Imaging and Photon Migration (OSA, Washington, DC). 3. Everett M J, Shoenenberger K, Colston B W and Da Silva L B 1998 Birefringence characterization of biological tissue by use of optical coherence tomography Opt. Lett. 23 228-30. 4. Shuliang J, Wurong Yu, Stoica G and Lihong V 2003 Optical fiber based Mueller optical coherence tomography Opt. Lett. 28 1206-08. 5. Coherent-Domain Optical Methods: Biomedical Diagnostics, Environmental and Material Science / edited by V. V. Tuchin // Laser Polarimetry of Biological Tissue. Principles and Applications / A.G. Ushenko, V.P. Pishak. – Boston: Kluwer Academic Publishers, p. 67-93 (2004). 6. A.G. Ushenko, Stokes-correlometry of biotissues // Laser Physics. 10, No.6, p.1-7 (2000). 7. A.G. Ushenko, Yu.Y. Tomka, Laser polarization selection of two-dimensional birefringence images // Proc. SPIE. 5972, p. 59720S (2005). 8. A.G. Ushenko, I.Z. Misevich, V. Istratiy and others. Evolution of statistic moments of 2D- distributions of biological liquid crystals net Mueller matrix elements in the process of their birefringent structure changes // Advances in Optical Technologies, 2010, Article 1D 423125 (2010). 9. O.V. Dubolazov, A.G. Ushenko, V.T. Bachunsky and others. On the feasibilities of using the wavelet analysis of Mueller matrix images of biological crystals. // Advances in Optical Technologies, 2010, Article 1D 162832 (2010). 10. A.G. Ushenko, 2D phase tomography of biotissues: II. Polarization visualization and selection of biotissue image two-layer scattering medium // Proc. SPIE, 5477, p. 450-456 (2004). 11. O.V. Angelsky; A.G. Ushenko; Ye.G. Ushenko, 2- D Stokes Polarimetry of Biospeckle Tissues Images in Pre-Clinic Diagnostics of Their Pre-Cancer States // Journal of Holography and Speckle, 2, (1), p. 26-33 (2005). 12. A.G. Ushenko; A.I. Fediv; Yu.F. Marchuk, Correlation and fractal structure of Jones matrices of human bile secret // Рroc. SPIE, 7368, 73681Q (2009). 13. A.G. Ushenko, Yu.Ya. Tomka, V.I. Istratiy, Polarization selection of two-dimensional phase- inhomogeneous birefringence images of biotissues // Рroc. SPIE, 7388, 73881L (2009). 14. Yu.Ya. Tomka, A.G. Ushenko, Yu. F. Marchuk, The degree of mutual correlation of coordinate distributions of Mueller matrix elements biological tissues and diagnostics of their physiological state // Рroc. SPIE, 7388, 73881K (2009). 15. A.G. Ushenko, Laser diagnostics of biofractals // Quantum Electronic,.29 (12), p.1-7 (1999). 16. A.G. Ushenko, The Vector Structure of Laser Biospeckle Fields and Polarization Diagnostics of Collagen Skin Structures // Laser Physics, 10 (5), p.1143-1149 (2000). 17. A.G. Ushenko, 2D phase tomography of biotissues: I. Topological structure value of birefringence // Рroc. SPIE, 5477, p.438-449 (2004). 18. A.G. Ushenko, Polarization introscopy of phase- inhomogeneous layers // Proc SPIE, 4900, p.1323- 1326 (2002). 19. O.V.Angelsky, A.G. Ushenko, Ye.G. Ushenko, Yu.Ya. Tomka, Polarization singularities of biological tissues images // J. Biomed. Opt. 11 (5), p. 054030 (2006). 20. A.G. Ushenko, Laser polarimetry of polarization- phase statistical moments of the objects field of optically anisotropic scattering layers // Optics and spectroscopy, 91 (2), p.313-317 (2001). 21. O.V. Angelsky, A.G. Ushenko, Ye.G. Ushenko, Investigation of the correlation structure of biological tissue polarization images during the diagnostics of their oncological changes // Phys. Med. Biol. 50, p.4811-4822 (2005). 22. O.V. Angelsky, V.P. Pishak, A.G. Ushenko, D.N. Burkovets, O.V. Pishak, Polarization-correlation investigation of biotissue multifractal structure and diagnostics of its pathological change // Рroc. SPIE, 4242, p.201-209 (2001). 23. O.V. Angelsky, A.G. Ushenko, Ye.G. Ushenko, Complex degree of mutual polarization of 104 http://www.ingentaconnect.com/content/asp/jhs;jsessionid=69dj5lalsprb1.alexandra http://spie.org/x648.xml?product_id=831559 http://spie.org/x648.xml?product_id=853298 http://spie.org/x648.xml?product_id=853298 http://bookstore.spie.org/index.cfm?fuseaction=detailpaper&cachedsearch=1&volume=11&fpage=054030&coden=JBOPFO&producttype=pdf&CFID=3429818&CFTOKEN=56766105 http://bookstore.spie.org/index.cfm?fuseaction=detailpaper&cachedsearch=1&volume=11&fpage=054030&coden=JBOPFO&producttype=pdf&CFID=3429818&CFTOKEN=56766105 Semiconductor Physics, Quantum Electronics & Optoelectronics, 2011. V. 14, N 1. P. 98-105. biological tissue coherent images for the diagnostics of their physiological state // J. Biomed. Opt. 10 (6), p. 060502 (2005). 24. A.G. Ushenko, S.B. Yermolenko, O.V. Angelsky, V.P. Pishak, O.V. Pishak, Laser polarimetry tomography of biotissue pathological changes // Рroc. SPIE, 4425, p.117-123 (2001). 25. A.G. Ushenko, A.I. Fediv, Yu.F. Marchuk, Singular structure of polarization images of bile secret in diagnostics of human physiological state // Рroc. SPIE, 73681S (2009). 26. S.B. Yermolenko, A.G. Ushenko, P. Ivashko, Spectropolarimetry of cancer change of biotissues // Рroc. SPIE, 7388,73881D (2009). 27. A.P. Peresunko, A.G. Ushenko, Analysis of statistical structure of bioliquid images into cancer diagnostics // Рroc. SPIE, 6254, 62541R (2006). 28. A.G. Ushenko, Polarization structure of scattering laser fields // Optical Engineerin. 34, (4), p.1088- 1093 (1995). 29. A.G. Ushenko, Depolarization of a laser emission field as the correlation development of its polarization structure // Proc. SPIE, 3317, p. 331 (1997); 30. A.G. Ushenko, Polarization contrast enhancement of images of biological tissues under the conditions of multiple scattering // Optics and Spectroscopy, 91, (6) p. 937-940 (2001). 31. A.G. Ushenko, VP. Pishak, S.B. Yermolenko, O.V. Pishak, D.N Burkovets, Laser measurements of crystal optical properties of blood-formed elements // Proc. SPIE, 3317, p.425-433 (1997). 32. A.G. Ushenko, Polarization correlometry of angular structure in the microrelief pattern or rough surfaces // Optics and spectroscopy, 92, (2), p.227 – 229 (2002). 33. A.G. Ushenko, Laser polarimetry of polarization- phase statistical moments of the object field of optically anisotropic scattering layers // Optics and Spectroscopy, 91, (2), p. 313-316 (2002). 34. A.G. Ushenko, Correlation processing and wavelet analysis of polarization images of biological tissues // Optics and Spectroscopy, 91, (5), p.773-778 (2002). 35. S. H. Guminetskiy; O. G. Ushenko; I. P. Polyanskiy; A. V. Motrych; F. V. Grynchuk, The optical method for investigation of the peritonitis progressing process // Proc. SPIE, 7008, p. 700827 (2008). 36. A.G. Ushenko, S.B.Yermolenko, A.G. Prydij, S.G. Guminetsky, Ion Gruia; Ovidiu Toma; K.S. Vladychenko, Statistical and fractal approaches in laser polarimetry diagnostics of the cancer prostate tissues // Proc. SPIE, 7008, p. 70082C (2008). 37. O. I. Olar, A. G. Ushenko, Polarization-correlation study of biotissue multifractal structure // Proc. SPIE, 5067, p. 41 - 49 (2003). 38. A.G. Ushenko, V.P. Pishak, O.V. Pishak, O.I. Olar, S.B. Yermolenko, A.G. Prydij, A. S. Arbuzov, Mueller matrices mapping of biological tissue architectonics // Proc. SPIE, 5477, p. 422 - 429 (2004). 39. O.V. Angelsky, A.G. Ushenko, I.M. Vashenko, L.M. Bodnar Study of polarizing intercorrelative function of coherent images of phase- inhomogeneous layer anisotropy // Proc. SPIE, 5856, p. 49 - 54 (2005). © 2011, V. 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