CAPES / Este trabalho apresenta a adaptação do código Geant4 para conversão de imagens DICOM (Digital Imaging and Communications in Medicine) de crânio, obtidas em tomografia convencional (CT), em um phantom antropomórfico virtual. O trabalho foi baseado no exemplo médico denominado “Código Dicom”, disponibilizado pelos desenvolvedores do código Geant4. Durante a execução do trabalho foram feitas reestruturações no exemplo “Código Dicom” para a conversão direta de imagens tomográficas em um phantom virtual. Foram retirados do código todos os passos referentes aos eventos físicos nucleares. Foi reformulado o arquivo DicomHandler.cc para não realizar a compressão dos pixels da imagem de CT. Em seguida foi realizada a conversão direta de imagens tomográficas, de um phantom físico de polietileno (PEAD) com núcleo central de acrílico e de um crânio real humano, em phantoms virtuais para o código Geant4. Os resultados demonstraram que com este código é possível a reconstrução de áreas anatômicas com geometrias complexas, partindo do uso de imagens tomográficas reais. / This work presents the adaptation of the Geant4 code for converting DICOM (Digital Imaging and Communications in Medicine) images of a skull, obtained in conventional tomography (CT), into a virtual anthropomorphic phantom. The work was based on the medical example named "Dicom Code" provided by the developers of the code Geant4. During the execution, restructurings using the "Dicom Code" example were made to achieve the direct conversion of tomographic images into a virtual phantom. All the steps referring to nuclear physical events were removed. The file DicomHandler.cc was reformulated in order to avoid the pixels compression of the CT image. The CT images of a physical polyethylene (PEAD) phantom with acrylic core and a real human skull were then converted into virtual phantoms for the code Geant4. The results showed that with this code, it may be possible the reconstruction of anatomical areas with complex geometries, based on the use of real tomographic images.

CNPq; CAPES / A termografia permite a visualização de valores de temperatura de um corpo por meio de imagens. Na área médica, encontra aplicações em oncologia, análise de queimaduras, doenças vasculares, doenças respiratórias, doenças de pele e como forma geral de verificação da vitalidade dos tecidos. A termografia 3D consiste de uma malha 3D com uma textura térmica projetada em sua superfície, oferecendo uma visualização mais precisa dos padrões de temperatura das estruturas anatômicas. Propõe-se, por meio do presente trabalho, um sistema capaz de combinar imagens termográficas 2D com sua malha 3D correspondente e, como resultado, entregar uma imagem termográfica 3D para aplicações médicas. Para isso foram utilizadas as técnicas de Otimização por Enxame de Partículas (PSO) e de reconstrução 3D Structure from Motion (SfM). Diferentemente de outros trabalhos na literatura, a malha 3D e as imagens térmicas não precisam ser adquiridas simultaneamente, não sendo necessário um arranjo mecânico dedicado. A malha 3D pode ter origem em um scanner 3D ou em uma imagem de ressonância magnética, por exemplo. Para avaliar os resultados, um phantom, isto é, um objeto estático de avaliação, com propriedades conhecidas, foi construído. Para tal, uma técnica inédita, utilizando placas de circuito impresso foi desenvolvida. Como resultado, comparações entre a saída do método proposto e o phantom, apresentaram um erro máximo de 3,73 mm e médio de 1,41 mm, com desvio padrão de 0,74 mm, em um phantom de 100 x 150 x 103,2 mm. / Thermography is an imaging method that allows temperature visualization of various regions of an object. In medicine, it finds applications related to oncology, burn trauma, vascular, respiratory and skin diseases, and as a general tissue vitality checking tool. 3D thermography adds tridimensional information to the conventional 2D thermography. It is made from a 3D mesh wrapped by thermal texture, enabling a more precise visualization of thermal patterns of anatomical structures. We propose a system capable of combining 2D thermal images with their corresponding 3D mesh, delivering a 3D thermogram for medical applications as a result. We used Particle Swarm Optimization (PSO) for mesh alignment and Structure from Motion (SfM) for 3D reconstruction in the present method. In contrast to most research found in the literature, the 3D mesh and the thermal images do not need to be acquired simultaneously, and a mechanical support for the thermal camera and the 3D scanner is not required. The 3D mesh may be acquired, for instance, from a 3D scanner or a magnetic resonance imaging machine. In order to evaluate the results, a phantom, that is, a static assessment object of known properties has been built. For this purpose, a novel technique using printed circuit boards has been developed. As a result, comparison between the output of the method and the phantom shows a maximum error of 3.73 mm and a mean error of 1.41 mm with 0.74 mm of standard deviation in phantom of 100 x 150 x 103.2 mm. / 5000

CNPq; CAPES / A termografia permite a visualização de valores de temperatura de um corpo por meio de imagens. Na área médica, encontra aplicações em oncologia, análise de queimaduras, doenças vasculares, doenças respiratórias, doenças de pele e como forma geral de verificação da vitalidade dos tecidos. A termografia 3D consiste de uma malha 3D com uma textura térmica projetada em sua superfície, oferecendo uma visualização mais precisa dos padrões de temperatura das estruturas anatômicas. Propõe-se, por meio do presente trabalho, um sistema capaz de combinar imagens termográficas 2D com sua malha 3D correspondente e, como resultado, entregar uma imagem termográfica 3D para aplicações médicas. Para isso foram utilizadas as técnicas de Otimização por Enxame de Partículas (PSO) e de reconstrução 3D Structure from Motion (SfM). Diferentemente de outros trabalhos na literatura, a malha 3D e as imagens térmicas não precisam ser adquiridas simultaneamente, não sendo necessário um arranjo mecânico dedicado. A malha 3D pode ter origem em um scanner 3D ou em uma imagem de ressonância magnética, por exemplo. Para avaliar os resultados, um phantom, isto é, um objeto estático de avaliação, com propriedades conhecidas, foi construído. Para tal, uma técnica inédita, utilizando placas de circuito impresso foi desenvolvida. Como resultado, comparações entre a saída do método proposto e o phantom, apresentaram um erro máximo de 3,73 mm e médio de 1,41 mm, com desvio padrão de 0,74 mm, em um phantom de 100 x 150 x 103,2 mm. / Thermography is an imaging method that allows temperature visualization of various regions of an object. In medicine, it finds applications related to oncology, burn trauma, vascular, respiratory and skin diseases, and as a general tissue vitality checking tool. 3D thermography adds tridimensional information to the conventional 2D thermography. It is made from a 3D mesh wrapped by thermal texture, enabling a more precise visualization of thermal patterns of anatomical structures. We propose a system capable of combining 2D thermal images with their corresponding 3D mesh, delivering a 3D thermogram for medical applications as a result. We used Particle Swarm Optimization (PSO) for mesh alignment and Structure from Motion (SfM) for 3D reconstruction in the present method. In contrast to most research found in the literature, the 3D mesh and the thermal images do not need to be acquired simultaneously, and a mechanical support for the thermal camera and the 3D scanner is not required. The 3D mesh may be acquired, for instance, from a 3D scanner or a magnetic resonance imaging machine. In order to evaluate the results, a phantom, that is, a static assessment object of known properties has been built. For this purpose, a novel technique using printed circuit boards has been developed. As a result, comparison between the output of the method and the phantom shows a maximum error of 3.73 mm and a mean error of 1.41 mm with 0.74 mm of standard deviation in phantom of 100 x 150 x 103.2 mm. / 5000

CAPES / Em vista do grande número de casos de câncer de mama e sua crescente taxa de incidência, novas técnicas de imagem estão sendo estudadas. No intuito de proporcionar melhores condições de visualização e detecção dessa doença, em complemento às informações obtidas por mamografia, as técnicas de imagem por contraste de fase vêm sendo investigadas. Assim, o objetivo do presente estudo, foi desenvolver um phantom de mama para aplicação em imagens por contraste de fase. Este phantom, é um cilindro com algumas inserções preenchidas por materiais equivalentes a tecidos mamários normais e patológicos, como: polimetilmetacrilato (PMMA), água, etanol, dimetilformamida e glicerol. Estes materiais foram escolhidos pela similaridade nas propriedades de atenuação e espalhamento dos tecidos mamários. Dentre as técnicas para evidenciar contraste de fase, foi utilizada a técnica de propagação. O arranjo experimental foi elaborado levando em consideração os cálculos para obtenção do contraste de fase utilizando a instrumentação para microtomografia de raios X do Instituto Lactec. Imagens radiográficas e microtomográficas foram adquiridas por transmissão e por contraste de fase e posteriormente comparadas. A comparação entre as imagens analisadas apresentaram significativas melhoras no contraste, principalmente nas bordas dos cilindros presentes no phantom. Portanto, o phantom desenvolvido neste trabalho pode ser utilizado para otimizar os parâmetros de aquisição e tratamento de imagens por contraste de fase para aplicação na detecção do câncer de mama. / Because of the large number of cases of breast cancer and its increasing incidence rate, new techniques of imaging are being studied. With the aim to provide better conditions for visualization and detection of this disease, in complement of the information obtained by mammography, the techniques of phase contrast imaging have been studied. Thus, the objective of the present study was to develop a breast phantom for application in phase contrast images. This phantom is a cylinder with some inserts filled with equivalent materials to normal and pathological breast tissues, such as: polymethylmethacrylate (PMMA), ethanol, dimethylformamide and glycerol. These materials were chosen due to the similarity in the attenuation and scattering properties of breast tissues. Among the techniques to demonstrate phase contrast, it was used the propagation technique. The experimental arrangement was elaborated taking into account the calculations to obtain the phase contrast using the instrumentation for X-ray microtomography of the Lactec Institute. Radiographic and microtomographic images were acquired by transmission and by phase contrast and then compared. The comparison between the analyzed images showed significant improvements in the contrast, mainly in the edges of the cylinders present in the phantom. Therefore, the phantom developed in this work can be used to optimize the acquisition and treatment parameters of phase contrast images for application in the detection of breast cancer.

A terapia com prótons está presente em 16 países e até 2015 tratou mais de 130 mil pacientes. No entanto, no Brasil essa terapia ainda não está presente por diversos motivos, sendo o principal o alto custo. Antes de realizar tratamentos, é necessário fazer alguns testes para verificação da entrega de energia dos feixes de prótons. Como as medidas de microdosimetria são muito caras, a principal alternativa é a realização de simulações em programas computacionais, como o GEANT4 e SRIM. O GEANT4 é um programa que permite simular geometrias complexas, enquanto que o SRIM realiza simulações mais simples e ambas trabalham com o método de Monte Carlo. Neste trabalho foram utilizadas estas duas ferramentas para realizar simulações de feixes de prótons em fantomas com três diferentes composições (água, água e tecido ósseo, tecido ósseo e cerebral). Para realizar a análise da entrega de energia dos feixes de prótons ao longo destes fantomas, tornou-se necessário criar um programa denominada “Programa de Processamento de Dados em Próton Terapia Simulada”, que proporcionou criar matrizes, além dos cálculos dos picos de Bragg para avaliação da interação. Além disso, foi analisada a homogeneidade da interação de um feixe de prótons em um detector, em que foi verificado que as simulações em GEANT4 são homogêneas, não tendo uma tendência do feixe em se localizar em uma determinada região, assim como as energias depositadas são iguais nas regiões do fantoma. Também foram avaliados os valores do alcance de profundidade dos picos de Bragg em fantomas cilíndricos com três diferentes densidades: 1,03 g/cm³, 1,53 g/cm³ e 2,03 g/cm³, sendo a primeira, a densidade fornecida pelo GEANT4 para tecido cerebral. Foi verificado que as distâncias do alcance de profundidade dos picos de Bragg são iguais nestas três diferentes densidades. / Proton therapy is present in 16 countries and by 2015 has treated more than 130,000 Patients. However, in Brazil this therapy is not yet present for several reasons, Being the main the high cost. Before performing treatments, it is necessary to do some tests to verify the energy delivery of the proton bundles. As the Microdosimetry are very expensive, the main alternative is to carry out simulations in Programs such as GEANT4 and SRIM. GEANT4 is a program that Allows you to simulate complex geometries, while SRIM performs more complex simulations. Simple and both work with the Monte Carlo method. On this work were used these twain tools to perform a proton beam simulation in phantom with three different compositions (water, bones and water, brain and bones). To perform the energy delivery analysis of the proton beams along these phantoms, has become necessary create a program denominated “Data Processing Program Proton Therapy Simulated”, which allowed to create matrices, beyond the calculations of the Bragg peaks for interaction evaluation. Besides that, it was analyzing the homogeneity of the integration of a proton beam into a detector, in which it was verified that the simulations on GEANT4 are homogeneous, not having a tendency of the beam in locating in a certain region, just as the energies deposited are equal. The value of the depth range of the Bragg peaks were also evaluated in cylindrical phantoms with three different densities: 1,03 g/cm³, 1,53g/cm³ and 2,03 g/cm³, the first being the density provided by GEANT4 for brain tissue. It has been found that the depth range distances of the Bragg peaks are the same at these three different densities.

A terapia com prótons está presente em 16 países e até 2015 tratou mais de 130 mil pacientes. No entanto, no Brasil essa terapia ainda não está presente por diversos motivos, sendo o principal o alto custo. Antes de realizar tratamentos, é necessário fazer alguns testes para verificação da entrega de energia dos feixes de prótons. Como as medidas de microdosimetria são muito caras, a principal alternativa é a realização de simulações em programas computacionais, como o GEANT4 e SRIM. O GEANT4 é um programa que permite simular geometrias complexas, enquanto que o SRIM realiza simulações mais simples e ambas trabalham com o método de Monte Carlo. Neste trabalho foram utilizadas estas duas ferramentas para realizar simulações de feixes de prótons em fantomas com três diferentes composições (água, água e tecido ósseo, tecido ósseo e cerebral). Para realizar a análise da entrega de energia dos feixes de prótons ao longo destes fantomas, tornou-se necessário criar um programa denominada “Programa de Processamento de Dados em Próton Terapia Simulada”, que proporcionou criar matrizes, além dos cálculos dos picos de Bragg para avaliação da interação. Além disso, foi analisada a homogeneidade da interação de um feixe de prótons em um detector, em que foi verificado que as simulações em GEANT4 são homogêneas, não tendo uma tendência do feixe em se localizar em uma determinada região, assim como as energias depositadas são iguais nas regiões do fantoma. Também foram avaliados os valores do alcance de profundidade dos picos de Bragg em fantomas cilíndricos com três diferentes densidades: 1,03 g/cm³, 1,53 g/cm³ e 2,03 g/cm³, sendo a primeira, a densidade fornecida pelo GEANT4 para tecido cerebral. Foi verificado que as distâncias do alcance de profundidade dos picos de Bragg são iguais nestas três diferentes densidades. / Proton therapy is present in 16 countries and by 2015 has treated more than 130,000 Patients. However, in Brazil this therapy is not yet present for several reasons, Being the main the high cost. Before performing treatments, it is necessary to do some tests to verify the energy delivery of the proton bundles. As the Microdosimetry are very expensive, the main alternative is to carry out simulations in Programs such as GEANT4 and SRIM. GEANT4 is a program that Allows you to simulate complex geometries, while SRIM performs more complex simulations. Simple and both work with the Monte Carlo method. On this work were used these twain tools to perform a proton beam simulation in phantom with three different compositions (water, bones and water, brain and bones). To perform the energy delivery analysis of the proton beams along these phantoms, has become necessary create a program denominated “Data Processing Program Proton Therapy Simulated”, which allowed to create matrices, beyond the calculations of the Bragg peaks for interaction evaluation. Besides that, it was analyzing the homogeneity of the integration of a proton beam into a detector, in which it was verified that the simulations on GEANT4 are homogeneous, not having a tendency of the beam in locating in a certain region, just as the energies deposited are equal. The value of the depth range of the Bragg peaks were also evaluated in cylindrical phantoms with three different densities: 1,03 g/cm³, 1,53g/cm³ and 2,03 g/cm³, the first being the density provided by GEANT4 for brain tissue. It has been found that the depth range distances of the Bragg peaks are the same at these three different densities.

Electrical Impedance Tomography (EIT) is a non linear inverse problem in which the electrical conductivity or resistivity distribution across a closed domain of interest is reconstructed from the surface potentials measured at the domain boundary by injecting a constant sinusoidal current through an array of surface electrodes. Being a non-invasive, non-radiating, non-ionizing, portable and inexpensive methodology, EIT has been extensively studied in medical diagnosis, biomedical engineering, biotechnology, chemical engineering, industrial and process engineering, civil and material engineering, soil and rock science, electronic industry, defense field, nano-technology and many other fields of applied physics. The reconstructed image quality in EIT depends mainly on the boundary data quality and the performance of the reconstruction algorithm used. The boundary data accuracy depends on the design of the practical phantoms, current injection method and boundary data measurement process and precision. On the other hand, the reconstruction algorithm performance is highly influenced by the mathematical modeling of the system, performance of the forward solver and Jacobian computation, inverse solver and the regularization techniques. Hence, for improving the EIT system performance, it is essential to improve the design of practical phantom, instrumentation and image reconstruction algorithm. As the electrical impedance of biological materials is a function of tissue composition and the frequency of applied ac signal, the better assessment of impedance distribution of biological tissues needs multifrequency EIT imaging. In medical EIT, to obtain a better image quality for a complex organ or a body part, accurate domain modelling with a large 3D finite element mesh is preferred and hence, the computation speed becomes very expensive and time consuming. But, the high speed reconstruction with improved image quality at low cost is always preferred in medical EIT. In this direction, a complete multifrequency multifunction EIT (MfMf-EIT) system is developed and multifrequency impedance reconstruction is studied to improve the bioimpedance imaging. The MfMf-EIT system consists of an MfMf-EIT instrumentation (MfMf-EITI), high speed impedance image reconstruction algorithms (IIRA), a Personal Computer (PC) and a number of practical phantoms with EIT sensors or electrodes. MfMf-EIT system and high speed IIRA are studied tested and evaluated with the practical phantoms and the multifrequency impedance imaging is improved with better image quality as well as fast image reconstruction. The MfMf-EIT system is also applied to the human subjects and the impedance imaging is studied for human body imaging and the system is evaluated. MfMf-EIT instrumentation (MfMf-EITI) consists of a multifrequency multifunction constant current injector (MfMf-CCI), multifrequency multifunction data acquisition system (MfMf DAS), a programmable electrode switching module (P-ESM) and a modified signal conditioner blocks (M-SCB) or data processing unit (DPU). MfMf-CCI, MfMf-DAS, P-ESM and M-SCBs are interfaced with a LabVIEW based data acquisition program (LV-DAP) controlled by a LabVIEW based graphical user interface (LV-GUI). LV-GUI controls the current injection and data acquisition with a user friendly, fast, reliable, efficient measurement process. The data acquisition system performance is improved by the high resolution NIDAQ card providing high precision measurement and high signal to noise ratio (SNR). MfMf-EIT system is developed as a versatile data acquisition system with a lot of flexibilities in EIT parameter selection that allows studying the image reconstruction more effectively. MfMf-EIT instrumentation controls the multifrequency and multifunctioned EIT experimentation with a number of system variables such as signal frequency, current amplitude, current signal wave forms and current injection patterns. It also works with either grounded load CCI or floating load CCI and collects the boundary data either in grounded potential form or differential form. The MfMf-EITI is futher modified to a battery based MfMf-EIT (BbMfMf-EIT) system to obtain a better patient safety and also to improve the SNR of the boundary data. MfMf-EIT system is having a facility of injecting voltage signal to the objects under test for conducting the applied potential tomography (APT). All the electronic circuit blocks in MfMf-EIT instrumentation are tested, evaluated and calibrated. The frequency response, load response, Fast Fourier Transform (FFT) studies and DSO analysis are conducted for studying the electronic performance and the signal quality of all the circuit blocks. They are all evaluated with both the transformer based power supply (TBPS) and battery based power supply (BBPS). MfMf-DAS, P-ESM and LV-DAP are tested and evaluated with digital data testing module (DDTM) and practical phantoms. A MatLAB-based Virtual Phantom for 2D EIT (MatVP2DEIT) is developed to generate accurate 2D boundary data for assessing the 2D EIT inverse solvers and its image reconstruction accuracy. It is a MATLAB-based computer program which defines a phantom domain and its inhomogeneities to generate the boundary potential data by changing its geometric parameters. In MatVP2DEIT, the phantom diameter, domain discretization, inhomogeneity number, inhomogeneity geometry (shape, size and position), electrode geometry, applied current magnitude, current injection pattern, background medium conductivity, inhomogeneity conductivity all are set as the phantom variables and are chosen indipendently for simulating different phantom configurations. A constant current injection is simulated at the phantom boundary with different current injection protocols and boundary potential data are calculated. A number of boundary data sets are generated with different phantom configurations and the resistivity images are reconstructed using EIDORS (Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software). Resistivity images are evaluated with the resistivity parameters and contrast parameters estimated from the elemental resistivity profiles of the reconstructed impedance images. MfMf-EIT system is studied, tested, evaluated with a number of practical phantoms eveloped with non-biological and biological materials and the multifrequency impedance imaging is improved. A number of saline phantoms with single and multiple inhomogeneities are developed and the boundary data profiles are studied and the phantom geometry is modified. NaCl-insulator phantoms and the NaCl-vegetable phantoms with different inhomogeneity configurations are developed and the multifrequency EIT reconstruction is studied with different current patterns, different current amplitudes and different frequencies using EIDORS as well as the developed IIRAs developed in MATLAB to evaluate the phantoms and MfMf-EIT system. Real tissue phantoms are developed with different chicken tissue backgrounds and high resistive inhomogeneities and the resistivity image reconstruction is studied using MfMf-EIT system. Chicken tissue phantoms are developed with chicken muscle tissue (CMTP) paste or chicken tissue blocks (CMTB) as the background mediums and chicken fat tissue, chicken bone, air hole and nylon cylinders are used as the inhomogeneity to obtained different phantom configurations. Resistivity imaging of all the real tissue phantoms is reconstructed in EIDORS and developed IIRAs with different current patterns, different frequencies and the images are evaluated by the image parameters to assess the phantoms as well as the MfMf-EIT system. Gold electrode phantoms are developed with thin film based flexible gold electrode arrays for improved bioimpedance and biomedical imaging. The thin film based gold electrode arrays of high geometric precision are developed on flexible FR4 sheet using electro-deposition process and used as the EIT sensors. The NaCl phantoms and real tissue phantoms are developed with gold electrode arrays and studied with MfMf-EIT system and and the resiulsts are compared with identical stainless steel electrode phantoms. NaCl phantoms are developed with 0.9% NaCl solution with single and multiple insulator or vegetable tissues as inhomogeneity. Gold electrode real tissue phantoms are also developed with chicken muscle tissues and fat tissues or other high resistive objects. The EIT images are reconstructed for the gold electrode NaCl phantoms and the gold electrode real tissue phantoms with different phantom geometries, different inhomogeneity configurations and different current patterns and the results are compared with identical SS electrode phantoms. High speed IIRAs called High Speed Model Based Iterative Image Reconstruction (HSMoBIIR) algorithms are developed in MATLAB for impedance image reconstruction in Electrical Impedance Tomography (EIT) by implementing high speed Jacobian calculation techniques using “Broyden’s Method (BM)” and “Adjoint Broyden’s Method (ABM)”. Gauss Newton method based EIT inverse solvers repeatitively evaluate the Jacobian (J) which consumes a lot of computation time for reconstruction, whereas, the HSMoBIIR with Broyden’s Methods (BM)-based accelerated Jacobian Matrix Calculators (JMCs) provides the high speed schemes for Jacobian (J) computation which is integrated with conjugate gradient scheme (CGS) for fast impedance reconstruction. The Broyden’s method based HSMoBIIR (BM-HSMoBIIR) and Adjoint Broyden’s method based HSMoBIIR (ABM-HSMoBIIR) algorithm are developed for high speed improved impedance imaging using BM based JMC (BM-JMC) and ABM-based JMC (ABM-JMC) respectively. Broyden’s Method based HSMoBIIR algorithms make explicit use of secant and adjoint information that can be obtained from the forward solution of the EIT governing equation and hence both the BM-HSMoBIIR and ABM-HSMoBIIR algorithms reduce the computational time remarkably by approximating the system Jacobian (J) successively through low-rank updates. The impedance image reconstruction is studied with BM-HSMoBIIR and ABM-HSMoBIIR algorithms using the simulated and practical phantom data and results are compared with a Gauss-Newton method based MoBIIR (GNMoBIIR) algorithm. The GNMoBIIR algorithm is developed with a Finite Element Method (FEM) based flexible forward solver (FFS) and Gauss-Newton method based inverse solver (GNIS) working with a modified Newton-Raphson iterative technique (NRIT). FFS solves the forward problem (FP) to obtain the computer estimated boundary potential data (Vc) data and NRIT based GNIS solve the inverse problem (IP) and the conductivity update vector [Δσ] is calculated by conjugate gradient search by comparing Vc measured boundary potential data (Vm) and using the Jacobian (J) matrix computed by the adjoint method. The conductivity reconstruction is studied with GNMoBIIR, BM-HSMoBIIR and ABM-HSMoBIIR algorithms using simulated data a practical phantom data and the results are compared. The reconstruction time, projection error norm (EV) and the solution error norm (Eσ) produced in HSMoBIIR algorithms are calculated and compared with GNMoBIIR algorithm. Results show that both the BM-HSMoBIIR and ABM-HSMoBIIR algorithms successfully reconstructs the conductivity distribution of the domain under test with its proper inhomogeneity and background conductivities for simulation as well as experimental studies. Simulated and practical phantom studies demonstrate that both the BM-HSMoBIIR and ABM-HSMoBIIR algorithms accelerate the impedance reconstruction by more than five times. It is also observed that EV and Eσ are reduced in both the HSMoBIIR algorithms and hence the image quality is improved. Noise analysis and convergence studies show that both the BM-HSMoBIIR and ABM-HSMoBIIR algorithms works faster and better in noisy conditions compared to GNMoBIIR. In low noise conditions, BM-HSMoBIIR is faster than to ABM-HSMoBIIR algorithm. But, in higher noisy environment, the ABM-HSMoBIIR is found faster and better than BM-HSMoBIIR. Two novel regularization methods called Projection Error Propagation-based Regularization (PEPR) and Block Matrix based Multiple Regularization (BMMR) are proposed to improve the image quality in Electrical Impedance Tomography (EIT). PEPR method defines the regularization parameter as a function of the projection error contributed by the mismatch (difference) between the data obtained from the experimental measurements (Vm) and calculated data (Vc). The regularization parameter in the reconstruction algorithm gets modified automatically according to the noise level in measured data and ill-posedness of the Hessian matrix. The L-2 norm of the projection error is calculated using the voltage difference and it is used to find the regularization parameter in each iteration in the reconstruction algorithm. In BMMR method, the response matrix (JTJ) obtained from the Jacobian matrix (J) has been partitioned into several sub-block matrices and the highest eigenvalue of each sub-block matrices has been chosen as regularization parameter for the nodes contained by that sub-block. The BMMR method preserved the local physiological information through the multiple regularization process which is then integrated to the ill-posed inverse problem to make the regularization more effective and optimum for all over the domain. Impedance imaging with simulated data and the practical phantom data is studied with PEPR and BMMR techniques in GNMoBIIR and EIDORS and the reconstructed images are compared with the single step regularization (STR) and Modified Levenberg Regularization (LMR). The projection error and the solution error norms are estimated in the reconstructions processes with PEPR and the BMMR methods and the results are compared with the errors estimated in STR and modified LMR techniques. Reconstructed images obtained with PEPR and BMMR are also studied with image parameters and contrast parameters and the reconstruction performance with PEPR and BMMR are evaluated by comparing the results with STR and modified LMR. PEPR and BMMR techniques are successfully implemented in the GNMoBIIR and EIDORS algorithms to improve the impedance image reconstruction by regularizing the solution domain in EIT reconstruction process. As the multifrequency EIT is always preferred in biological object imaging for better assessments of the frequency dependent bioimpedance response, multifrequency impedance imaging is studied with MfMf-EIT system developed for biomedical applications. MfMf-EIT system is studied, tested and evaluated with practical phantoms suitably developed for multifrequency impedance imaging within a wide range of frequency. Different biological materials are studied with electrical impedance spectroscopy (EIS) and a number of practical biological phantoms suitable for multifrequency EIT imaging are developed. The MfMf-EIT system is studied, tested and evaluated at different frequency levels with different current patterns using a number of NaCl phantoms with single, multiple and hybrid vegetable tissue phantoms as well as with chicken tissue phantoms. BbMfMf-EIT system is also studied and evaluated with the multifrequency EIT imaging using the developed biological phantoms. The developed MfMf-EIT system is applied on human body for impedance imaging of human anatomy. Impedance imaging of human leg and thigh is studied to visualize the muscle and bone tissues using different current patterns and different relative electrode positions. Ag/AgCl electrodes are attached to the leg and thigh using ECG gel and the boundary data are collected with MfMf-EIT EIT system by injecting a 1 mA and 50 kHz sinusoidal constant current with neighbouring and opposite current injection patterns. Impedance images of the femur bone of the human thigh and the tibia and fibula bones of the human leg along with the muscle tissue backgrounds are reconstructed in EIDORS and GNMoBIIR algorithms. Reconstructed resistivity profiles of bone and muscles are compared with the resistivity data profiles reported in the published literature. Impedance imaging of leg and thigh is studied with MfMf-EIT system for different current patterns, relative electrode positions and the images are evaluated to assess the system reliability. Battery based MfMf-EIT system (BbMfMf-EIT) is also studied for human leg and thigh imaging and it is observed that MfMf-EIT system and BbMfMf-EIT system are suitable for impedance imaging of human body imaging though the BbMfMf-EIT system increases the patiet safety. Therefore, the developed MfMf-EIT and BbMfMf-EIT systems are found quite suitable to improve the bio-impedance imaging in medical, biomedical and clinical applications as well as to study the anatomical and physiological status of the human body to diagnose, detect and monitor the tumors, lesions and a number of diseases or anatomical abnormalities in human subjects.