Image reconstruction technologies for protein spot parametrisation ; Vaizdo rekonstravimo technologijos baltymų pėdsakams parametrizuoti
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Image reconstruction technologies for protein spot parametrisation ; Vaizdo rekonstravimo technologijos baltymų pėdsakams parametrizuoti

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VILNIUSGEDIMINASTECHNICALUNIVERSITYArtūrasSERACKISIMAGERECONSTRUCTIONTECHNOLOGIESFORPROTEINSPOTPARAMETRISATIONSummaryofDoctoralDissertationTechnologicalSciences, ElectricalandElectronicEngineering(01T)Vilnius 2008Doctoral dissertation was prepared at Vilnius Gediminas Technical University in2004–2008.Scientific SupervisorProfDrDaliusNAVAKAUSKAS(VilniusGediminasTechnicalUniversity,Tech-nological Sciences, ElectricalandElectronic Engineering –01T).ThedissertationisbeingdefendedattheCouncilofScientificFieldofElectricalandElectronicEngineeringatVilniusGediminasTechnicalUniversity:ChairmanProf Dr Habil Stanislovas ŠTARAS (Vilnius Gediminas Technical University,Technological Sciences, ElectricalandElectronic Engineering –01T).Members:ProfDrHabilDanieliusEIDUKAS (KaunasUniversity ofTechnology, Techno-logical Sciences,ElectricalandElectronic Engineering –01T),Prof Dr Habil Algimantas KAJACKAS (Vilnius Gediminas Technical Univer-sity, Technological Sciences, ElectricalandElectronic Engineering –01T),Assoc Prof Dr Antanas Leonas LIPEIKA (Institute of Mathematics and Infor-matics, Technological Sciences,InformaticsEngineering –07T),ProfDrHabilJuliusSKUDUTIS(VilniusGediminasTechnicalUniversity,Tech-nological Sciences, ElectricalandElectronic Engineering –01T).

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Publié le 01 janvier 2009
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VILNIUS GEDIMINAS TECHNICAL UNIVERSITY
Artūras SERACKIS
IMAGE RECONSTRUCTION TECHNOLOGIES FOR PROTEIN SPOT PARAMETRISATION
Summary of Doctoral Dissertation Technological Sciences, Electrical and Electronic Engineering (01T)
Vilnius
2008
Doctoral dissertation was prepared at Vilnius Gediminas Technical University in 2004–2008. Scientific Supervisor Prof Dr Dalius NAVAKAUSKAS(Vilnius Gediminas Technical University, Tech-nological Sciences, Electrical and Electronic Engineering – 01T). The dissertation is being defended at the Council of Scientific Field of Electrical and Electronic Engineering at Vilnius Gediminas Technical University: Chairman Prof Dr Habil Stanislovas ŠTARAS(Vilnius Gediminas Technical University, Technological Sciences, Electrical and Electronic Engineering – 01T). Members: Prof Dr Habil Danielius EIDUKAS(Kaunas University of Technology, Techno-logical Sciences, Electrical and Electronic Engineering – 01T), Prof Dr Habil Algimantas KAJACKAS(Vilnius Gediminas Technical Univer-sity, Technological Sciences, Electrical and Electronic Engineering – 01T), Assoc Prof Dr Antanas Leonas LIPEIKA(Institute of Mathematics and Infor-matics, Technological Sciences, Informatics Engineering – 07T), Prof Dr Habil Julius SKUDUTIS(Vilnius Gediminas Technical University, Tech-nological Sciences, Electrical and Electronic Engineering – 01T). Opponents: Prof Dr Habil Romanas MARTAVIČIUS(Vilnius Gediminas Technical Univer-sity, Technological Sciences, Electrical and Electronic Engineering – 01T), Assoc Prof Dr Rimantas PUPEIKIS(Institute of Mathematics and Informatics, Physical Sciences, Informatics – 09P).
The dissertation will be defended at the public meeting of the Council of Scientific Field of Electrical and Electronic Engineering in the Senate Hall of Vilnius Gedimi-nas Technical University at 1 p.m. on 19 December 2008. Address: Saulėtekio al. 11, LT-10223 Vilnius, Lithuania. Tel. +370 5 274 49 52, +370 5 274 49 56; fax +370 5 270 01 12; e-mail: doktor@adm.vgtu.lt The summary of the doctoral dissertation was distributed on 18 November 2008. A copy of the doctoral dissertation is available for review at the Library of Vilnius Gediminas Technical University (Saulėtekio al. 14, LT-10223 Vilnius, Lithuania).
© Artūras Serackis, 2008
VILNIAUS GEDIMINO TECHNIKOS UNIVERSITETAS
Artūras SERACKIS
VAIZDO REKONSTRAVIMO TECHNOLOGIJOS BALTYMŲ PĖDSAKAMS PARAMETRIZUOTI
Daktaro disertacijos santrauka Technologijos mokslai, elektros ir elektronikos inžinerija (01T)
Vilnius
2008
Disertacija rengta 2004–2008 metais Vilniaus Gedimino technikos universitete. Mokslinis vadovas prof. dr. Dalius NAVAKAUSKAS(Vilniaus Gedimino technikos universitetas, technologijos mokslai, elektros ir elektronikos inžinerija – 01T). Disertacija ginama Vilniaus Gedimino technikos universiteto Elektros ir elekt-ronikos inžinerijos mokslo krypties taryboje: Pirmininkas prof. habil. dr. Stanislovas ŠTARAS(Vilniaus Gedimino technikos universitetas, technologijos mokslai, elektros ir elektronikos inžinerija – 01T). Nariai: prof. habil. dr. Danielius EIDUKAS(Kauno technologijos universitetas, techno-logijos mokslai, elektros ir elektronikos inžinerija – 01T), prof. habil. dr. Algimantas KAJACKAS(Vilniaus Gedimino technikos univer-sitetas, technologijos mokslai, elektros ir elektronikos inžinerija – 01T), doc. dr. Antanas Leonas LIPEIKA(Matematikos ir informatikos institutas, tech-nologijos mokslai, informatikos inžinerija – 07T), prof. habil. dr. Julius SKUDUTIS(Vilniaus Gedimino technikos universitetas, technologijos mokslai, elektros ir elektronikos inžinerija – 01T). Oponentai: prof. habil. dr. Romanas MARTAVIČIUS(Vilniaus Gedimino technikos uni-versitetas, technologijos mokslai, elektros ir elektronikos inžinerija – 01T), doc. dr. Rimantas PUPEIKIS(Matematikos ir informatikos institutas, fiziniai mokslai, informatika – 09P).
Disertacija bus ginama Elektros ir elektronikos inžinerijos mokslo krypties tarybos posėdyje 2008 m. gruodžio 19 d. 13 val. Vilniaus Gedimino technikos universiteto senato posėdžių salėje. Adresas: Saulėtekio al. 11, LT-10223 Vilnius, Lietuva. Tel.: +370 5 274 49 52, +370 5 274 49 56; faksas +370 5 270 01 12; el. paštas doktor@adm.vgtu.lt Disertacijos santrauka išsiuntinėta 2008 m. lapkričio mėn. 18 d. Disertaciją galima peržiūrėti Vilniaus Gedimino technikos universiteto biblioteko-je (Saulėtekio al. 14, LT-10223 Vilnius, Lietuva). VGTU leidyklos „Technika“ 1550-M mokslo literatūros knyga.
© Artūras Serackis, 2008
INTRODUCTION Topicality of the Research Work Analysis of the proteins gives the possibility to analyse the health state of liv-ing organisms. In proteomics two-dimensional electrophoresis (2DE) is used for protein separation in the gel according to their isoelectric point (pI) and molecular mass (MM). This enables the bioengineer to analyse health state of the patient and to watch changes of the organism during the cure. The detected changes of the pro-teins in the samples, used for 2DE, makes it possible to watch the influence of the applied medical treatment to the patient after some period of time. An automatic protein spot detection and parametrisation is able to help the expert to make com-parisons of two different 2DE gels and quickly identify the type and amount of the protein appeared or disappeared in the gel. Number of 2DE gel analysis systems uses image processing techniques for protein spot detection and parametrisation in the scanned gel images (see Fig 1). Though the fully automatic protein spot detection and parametrisation is still not possible.
Isoelectric Point,pI
Fig 1.2DE gel image The 2DE gel analysis systems are not able to deal with specific protein spot distortions found in the gel images. The over-saturated protein spots prevent proper segmentation of the 2DE gel images. Automatic detection and reconstruction of the over-saturated protein spots is impossible using available protein analysis soft-ware. The expensive 2DE experiment has to be repeated. The neighbouring protein spots may overlap in 2DE gel images. The proper parametrisation of such spots is impossible due to influence of neighbouring spots to each other shape. The segmented region can cover only the part of the over-lapped spots, making the parametrisation hard.
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Statement of the Problem About 10 000 various proteins may appear in one 2DE gel of size 40×30 cm. Analysis and comparison of such gels is complicated and time consuming. Auto-matic 2DE gel analysis systems can be made by combining computer performance and modern digital image processing techniques. The result of 2DE process has to be scanned with high sensitivity scanner for the further image analysis. Various ar-tifacts, donuts, scratches are often present in 2DE gel images. The additional 2DE process for the same sample in most cases is not possible due to expensivity of the ingredients used. The image processing techniques, applied for the scanned gel, has to be flexible and tunable to omit the influence of the all distortions present in the image. Number of programs for 2DE gel image analysis are powerful and precise for detection and parametrisation of the undistorted protein spots. Because of the unavoidable distortions, present in the 2DE gel images, those programs works in semiautomatic mode. To fully automate the 2DE gel image analysis process, the new methods for distorted protein spot analysis has to be developed. The detail analysis and parametrisation of the complicated protein spots can not be found in literature. No methods were proposed and implemented for pro-cessing and analysis of such gel images for proteins parametrisation. To solve the problem presented above the hypothesis is stated: By the use of the modern image reconstruction technologies for protein para-metrisation in 2DE gel images it is possible to perform: Gcorrect parametrisation of saturated protein spots; Gidentification and reconstruction of over-saturated protein spots; Gparametrisation of the overlapped protein spots. The Aim of the Work The aim of this work is to investigate the possibility of image reconstruction technologies applications for object parametrisation by creation and investigation of methods for protein spot parametrisation in 2DE gel images. Tasks of the Work On purposed aim of the work the three tasks has to be solved: 1. Propose mathematical models for parametrisation of saturated protein spots in 2DE gel images. 2. Develop and investigate methods for the over-saturated protein spots de-tection and reconstruction in the 2DE gel images. 3. Develop and investigate methods for the overlapped protein spots paramet-risation in the 2DE gel images.
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Research Object The research object is the digital 2DE gel images with three types of image regions: saturated protein spots with flat top; over-saturated protein spots with cave; overlapped protein spots. Applied Methods The methods used in this work are as follows: digital image processing, three-dimensional modelling and reconstruction, Radial Basis Function (RBF) networks. The protein spot models and methodologies presented in this work were build by the use of MATLABTM. Scientific Novelty The scientific novelty of this dissertation is following: 1. The original the-dimensional mathematical models, based on two-dimen-sional well known functions, were suggested for the ordinary and saturated protein spots modelling in 2DE gel images. 2. The methodology for the over-saturated protein spots detection, based on correlation techniques, and reconstruction, using original reconstruction algorithm and mathematical model of the protein spot, were developed. 3. The methodology for the overlapped protein spots parametrisation by the use of RBF networks for 2DE gel image reconstruction were developed. Presented for Defence 1. The suggested original mathematical models are suitable for ordinary and saturated protein spots modelling and can be fitted faster comparing to analogical Diffusion model. 2. The developed methodology of the over-saturated protein spot detection and reconstruction is able to detect and reconstruct overlapped protein spots, prevented proper image segmentation of the 2DE gel images. 3. The developed methodology of protein spot reconstruction using RBF net-works is suitable for overlapped protein spots parametrisation in 2DE gel images. Links with Scientific Programmes The results of investigation are applied in: Fscientific project No. T-08126 „Development of Parametrisation and Sys-
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tematic Catalogue System for Two-Dimensional Gel Images“ (2008); Fscientific work of Vilnius Gediminas Technical University No. 2.42 ELES 01T „Investigation on Computational Intelligence Technologies for Signal Processing“ (2008-2012); Fscientific work of Vilnius Gediminas Technical University „Improvement of Nonlinear Digital Signal Processing Technologies“ (2005–2007); Fscientific work of Vilnius Gediminas Technical University „Improvement of Digital Processing Technologies of Video and Audio Signals“ (2004). Approval of the Work Twelve scientific papers have been published on the topic of this work: two papers in the prestigious national journal quoted in the Thomson ISI Web of Sci-ence [1, 2], one paper in the prestigious national journal quoted in the international database Inspec [3], one paper in the conference proceedings quoted in the inter-national database Inspec [4], two papers in periodical reviewed journals published aboard [5, 6], three papers in periodical reviewed proceedings of the international conference [7, 8, 9] and three papers in the proceedings of national conferences [10, 11, 12]. Research results were used in the technical reports on three scien-tific works. The main results of the thesis were reported at the following scientific conferences: FInternational IEEE Workshop „Bio-Inspired Signal and Image Processing“, 2008, Warshaw, Poland. FInternational Conference „Electronics“, 2005–2008, Vilnius. FInternational Conference „trans&MOTAUTO“, 2005, Sofia, Bulgaria. FInternational Conference on Fundamentals of Electrotechnics and Cirquit Theory „IC-SPETO’2006“, 2006, Gliwice, Poland. FIX International PhD Workshop „OWD’2007“, 2007, Wisla, Poland. F– the Future of Lithuania“, 2005–Young Scientist Conference „Science 2007, Vilnius. FInternational Conference „Modern Information Technology“, 2005, Braslav, Belarus. The Scope of the Scientific Work The dissertation is written in Lithuanian. The explanatory part takes up 136 pa-ges. The work contains 68 mathematical expressions, 55 figures, 3 tables, 3 al-gorithms, cites 151 references. The thesis consists of introduction, four chapters, generalisation of the results, and two Appendices – Tools for Image Analysis and Vocabulary of Terms. The index of main concepts are presented here as well.
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CONTENT OF DISSERTATION Image Reconstruction Methods Review Object parametrisation is performed by the use of special equipment. The re-flections of various types of waves from the object are measured or the images, taken from different view angle are analysed. During analysis of object images, the characteristic points coordinates in three-dimensional space are calculated. The parametrisation of the objects are made by the analysis of estimated characteristic points in three-dimensional space. Stereo-reconstruction is widely used for object three-dimensional model reconstruction for parametrisation. The detection of the characteristic points two views of the object depends on the chosen viewpoint: C. Harris and M. Stephens corner detector is able to detect characteristic points in the viewpoint range [0, 60]; point matching in two images, using widely used cross-correlation techniques gives accurate results when object view angle in two images differs less than 15(in special case – less than 20). The viewpoint of the protein spots in 2DE gel images is 0and does not change. Though the parametrisa-tion techniques, used in stereo-reconstruction cannot be applied. The point match-ing technique, used for stereo-reconstruction can be applied for overlapped protein spots search in 2DE gel images.
250 250 200 200 150 150 100 100 50 50 0 0 0 40 0 40 20 20 50 0 50 0 Fig 2.view of the over-saturated protein spot before and afterThree-dimensional the reconstruction
Protein spots in 2DE gel images has to be detected and parametrised. For parametrization of the protein spots the 2DE gel images are segmented into regions with one possible protein spot in each. Most widely used 2DE image segmentation method is based on regional minima search and watershed transformation. For each image segment the mathematical model of protein spot is applied. The overlapped protein spots (see Fig 2) can be separated only when peaks of intensities are detected for each protein spot. Though no method is proposed for parametrisation of overlapped spots. 9
There are several protein spot shape models used for protein spot detection and parametrisation proposed in literature. For undistorted protein spots, the An-isotro ic Gaussian shape model is used. For saturated protein spot detection and parametrisation the Diffusion shape model is used. Models of the Protein Spots for 2DE Gel Image Reconstruction The shape models for saturated protein spots have to meet four requirements: 1) suitability for parametrisation of protein spots, varying in size; 2) suitability for parametrisation of saturated protein spots (see Fig 3); 3) suitability for parametri-sation of asymmetric protein spots; 4) resistance to the non-protein spots by giving high approximation error. According to the stated requirements four protein spot shape models were ro osed.
250 200 150 100 50 500 4050 30 40 20 30 10 10 20 0 0 Fig 3.Saturated protein spot
Definition 1(Anisotropic Bell shape model) Anisotropic Bell spot shape model, used for parametrisation of protein spot in 2DE gel image segment with indices of the image points set byxandy, is expressed: Is S2VF(x y) =B1++xx2qx1 +ly1yc 2qy,(1) c lxyhereB– background intensity of the 2DE gel image;Is– intensity of the spot; ls(lx ly)– distance to the centre of the spot;qxandqy– inclination of the spot shape slope;cc(xc yc)– centre of the protein spot.
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Definition 2(Four splines shape model) Four splines spot shape model, used for parametrisation of protein spot in 2DE gel segment with indices of the image points set byxandy, is: S4S(x y) =B+IsSESW,SNSS,(2a) 0whenxa; SE=(x2c(2x(bxxcaxab)bxx2)2x)2whenax< xc(abxx2+x)c<bxx)x2c;bx; 1xc1(xax)2nwehwehnx(>axx+cxbx; (2b) 1whenxc+cx< xdx; 1 2 (xccx)2dx< x(dx+xc+cx)2; SW=2((xxc+dxc)2xdxx)2when (xc+cxdx)2when (dx+xc+cx)2< xxc+cx; (2c) 0whenyay; SN=(1yc2 (2y(ybcyaya)byy2)2y)2whenay< y(ay+ycby)2; yc 1(byay)2whenhwney(>ayy+cycby;by)2< yycby; (2d) 1whenydy; 12 (yc+cyy)2when SS=(yc(+2(yyc+dydc)yy2)2dy)2whend(ydy<+yyc+(cdyy)+y2c<+cyy)y2c+;cy; 0cywheny > yc+cy(2e) here:B– background intensity of the 2DE gel image;Is– intensity of the spot; ax ay dxanddy– parameters forming the bottom part of the shape; formą; bx by cxandcy– parameters forming the top of the shape.
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