Biomedical Image Processing / Medical Image Processing
Sina Shamekhi; Mohammad Hosein Miranbeigi; Ali Gooya
Volume 12, Issue 4 , January 2019, , Pages 265-275
Abstract
Matching of the protein spots in two dimensional gel electrophoresis (2DGE) images is a main process of analyzing these images. Due to the challenges of 2DGE images such as the presence of noise and artifacts, the matching of protein spots is performed under human supervision. This supervision involves ...
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Matching of the protein spots in two dimensional gel electrophoresis (2DGE) images is a main process of analyzing these images. Due to the challenges of 2DGE images such as the presence of noise and artifacts, the matching of protein spots is performed under human supervision. This supervision involves human errors. Therefore, in this work a new automated algorithm has been proposed for spot matching in 2DGE images which is based on a probabilistic model. Due to the complexities of the proposed model, the Variational Bayes has been used to solve the equations of the model. The performance of the proposed algorithm has been evaluated on real and synthetic 2DGE images with some statistical criteria. Protein spots in real image dataset have been matched by the proposed method with angular error of 0.05 and end point error of 1.46 and in synthetic image dataset with angular error of 0.13 and end point error of 0.90. These results reveal higher precision and effectiveness and lower matching error of the proposed method.
Biomedical Image Processing / Medical Image Processing
Sina Shamekhi; Mohammad Hossein Miranbaygi; Ali Gooya; Bahare Azarian
Volume 8, Issue 2 , June 2014, , Pages 183-202
Abstract
Two-dimensional gel electrophoresis (2DGE) is a basic and widely used method in proteomics. In this method, mixtures of proteins are separated due to the differences in their molecular weight and isoelectric points and a final image obtained from the separated protein spots is created. Due to the large ...
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Two-dimensional gel electrophoresis (2DGE) is a basic and widely used method in proteomics. In this method, mixtures of proteins are separated due to the differences in their molecular weight and isoelectric points and a final image obtained from the separated protein spots is created. Due to the large number of the protein spots in a 2DGE image and the importance of separation of overlapping proteins, the image processing of these images is a complex process. 2DGE images pose various noises and artifacts such as cracks, staining artifacts, and streaks that affect the reliability of the analysis. In this work, we have proposed a novel spots filter based on the scale-space second order structural Hessian and its eigenvalues for enhancing and separating the spots from the background. Furthermore, in this work, 2DGE images have been segmented and the locations of the spots have been detected. To evaluate and compare the proposed method, we have implemented three methods: Otsu thresholding, Watershed transform, and the method proposed by Mylona et al. Based on the regional spot volume evaluation, the TPR and FPR of the proposed method are 78.6 and 14.9, the TPR and FPR of the Otsu method are equal to 71.4 and 25.7 percent, and the TPR and FPR of the Watershed algorithm are 53.9 and 8.1 percent, respectively. Also, in the spot counts evaluation, the Precision and TPR of the proposed method are equal to 83.6 and 81.1 percent, and the Precision and TPR of Otsu method are 65.4 and 78.3, respectively. The Watershed transform has detected the spots with Precision and TPR equal to 27.7 and 68.2 percent, and the Precision and TPR of the method proposed by Mylona et al. are 74.0 and 72.7 percent, respectively. The results reveal the accuracy and superiority of the proposed method.
Targeted Drug Delivery / Smart Drug Delivery / Drug Targeting
Nadia Naghavi; Amene Sazgarnia; Mohammad Hossein Miranbaygi
Volume 4, Issue 3 , June 2010, , Pages 209-218
Abstract
Today, the idea of photodynamic therapy (PDT) is considered as one of the fundamental basis of the new cancer treatment methods. One of the important issues in the application of this therapy is choosing the optimal dosimetry method. At best, PDT dosimetry should be done based on estimation of the accumulated ...
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Today, the idea of photodynamic therapy (PDT) is considered as one of the fundamental basis of the new cancer treatment methods. One of the important issues in the application of this therapy is choosing the optimal dosimetry method. At best, PDT dosimetry should be done based on estimation of the accumulated singlet oxygen dose within the target tissue and comparison with the threshold value to ensure the efficacy of the treatment. In order to estimate the accumulated singlet oxygen level within the tissue, the most appropriate method is modeling the process of treatment. In this context, it is necessary to obtain enough information about the drug concentration within the target tissue, the amount of light absorbed by the drug, the amount of oxygen into the tissue, and the interactions between them that produce singlet oxygen. In this study modeling and simulation of the photobleaching has been investigated, considering the importance of the level of drug concentration in the target tissue which would be decreased by photobleaching. Simulation was done with Matlab software. A Comparison of simulation results with those of experimental methods showed that in the state of non-uniform drug distribution, simulation follows experimental results at the initial phase of rapid decline of drug concentration.
Zohre Dehghani Bidgoli; Mohammad Hossein Miranbaygi; Rasoul Malekfar; Ehsanollah Kabir; Tahere Khamechian
Volume 4, Issue 4 , June 2010, , Pages 307-316
Abstract
In this research, we investigated cancerous tissues from several organs of the human body using Raman spectroscopy. Different specimens with different pathologic labels (normal & cancerous) were borrowed from a pathology laboratory, and were investigated using two different Raman spectroscopy systems. ...
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In this research, we investigated cancerous tissues from several organs of the human body using Raman spectroscopy. Different specimens with different pathologic labels (normal & cancerous) were borrowed from a pathology laboratory, and were investigated using two different Raman spectroscopy systems. Since one of the goals of this investigation was detection of cancer, independent of type of the system, we introduced some algorithms for removing systemic differences from the spectra. Then we removed noise and fluorescence signals using a new wavelet created with LWT. The best classification result was 83% in differentiating between normal and cancerous specimens using the SVM classifier
Biomedical Image Processing / Medical Image Processing
Mohammad Hosein Miranbeigi; Leila Mohammadi; Sahar Moghimi; Giti Torkaman
Volume 3, Issue 1 , June 2009, , Pages 15-24
Abstract
Collagen content and its configuration are considered to be among important criteria of healing in tissues. Therefore, developing a method to estimate these factors can benefit physicians in terms of valuable information. In this paper, we examine variation of collagens in tissue mimicking phantoms as ...
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Collagen content and its configuration are considered to be among important criteria of healing in tissues. Therefore, developing a method to estimate these factors can benefit physicians in terms of valuable information. In this paper, we examine variation of collagens in tissue mimicking phantoms as well as in vivo tissue taking advantage of applying image processing techniques on ultrasound images of samples. In phantoms, as the base tissue we have used agar-water matrix material and graphite to simulate collagen, respectively. We also have used different concentrations of graphite to simulate different contents of collagen according to attenuation coefficient of ultrasound waves in soft tissue and its correlation with weight ratio of graphite. Experimental and simulation results show that increase in concentration of graphite in phantoms results in higher energy and more contrast level in B-Mode images (r=0.99, p
Biological Computer Modeling / Biological Computer Simulation
Pejman Ghassemi; Mohammad Hossein Miranbaygi
Volume 2, Issue 4 , June 2008, , Pages 305-315
Abstract
In this research we present a new method to evaluate changes in size and refractive index of Titanium dioxide (TiO2) nanoparticles which are the main component of anti-UV creams. The main objective of this research is assessing the impact of changing in size and refractive index of TiO2 on the polarization ...
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In this research we present a new method to evaluate changes in size and refractive index of Titanium dioxide (TiO2) nanoparticles which are the main component of anti-UV creams. The main objective of this research is assessing the impact of changing in size and refractive index of TiO2 on the polarization state of backscattered light. The proposed technique is based on modeling the propagated polarized laser beam inside a phantom and evaluating the change in the polarization of backscattered light. The phantom is simulated by software to have the polarization properties of anti-UV creams. As scattering particles (TiO2) in these creams configure polarization properties, then through modeling we have simulated the phantom with matrix of resin epoxy that has unit refractive index including Titanium dioxide nanoparticles. It will be shown that size parameter and relative refractive index of these particles influence cream's properties like purity, quality, coating power and degree of filtration and directly affect its polarization properties. The measurement technique which is presented here is based on scattering polarimetry. To assess the scattering phenomenon, the polarization state of incident and backscattered light is analyzed by simulating a laboratory polarimeter. Then polarization information of the simulated phantom is extracted as Mueller matrix and degree of polarization index. All modeling and simulations are performed in MATLAB 2006 and the results are presented towards the end part of the paper. The main outcome of this research is the ability of extracting and the recognition of those elements of the Mueller matrix which are very sensitive to changes in size parameter and relative refractive index of TiO2. That will define the main markers for quality assessment of anti-UV creams.
