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    Image Registration Using a Total Variation Based Similarity Metric

    , Ph.D. Dissertation Sharif University of Technology Aghajani, Khadijeh (Author) ; Manzouri Shelmani, Mohammad Taghi (Supervisor)
    Image registration is one of the fundamental and essential tasks for medical imaging and remote sensing applications. One of the most common challenges in this area is the presence of complex spatially varying intensity distortion in the images. The widely used similarity metrics, such as MI (Mutual Information), CC (Correlation Coefficient), SSD (Sum of Square Difference), SAD (Sum of Absolute Difference) and CR (Correlation Ratio), are not robust against this kind of distortion; because stationarity assumption and the pixel-wise independence cannot be obeyed and captured by these metrics. In this research, we proposed a new intensity-based method for simultaneous image registration and... 

    Intra-Operative Registration of Non-Rigid Tissue for Image-Guided Surgery

    , M.Sc. Thesis Sharif University of Technology Amiri, Hakimeh (Author) ; Kasaei, Shohreh (Supervisor)
    Image Registration is a fundamental task in numerous applications in medical image processing and is defined as the process of determining the correspondence of between images collected at different times or using different imaging modalities. This correspondence can be used for aligning images so that the pair can be directly compared, combined or analyzed. Image-guided surgery systems use registration for establishing an accurate relation between preoperative and intraoperative image space. There have been several methods for rigid registration which are not easily applicable for soft tissues. Indeed, nonrigid deformation of soft tissues will endanger the accuracy of rigid methods, so it... 

    Registration of MRI-CT Images of the Human Brain using Deep Learning

    , M.Sc. Thesis Sharif University of Technology Ansarino, Keyvan (Author) ; Fatemizadeh, Emadeddin (Supervisor)
    Image registration is the process of matching the coordinate systems of two or more images. Medical image registration has been used in a variety of applications such as segmentation, motion tracking and etc. Recently, the use of deep neural networks has been demonstrated as a useful approach to registration problems. In this work, we propose two separate novel Convolutional Neural Network (CNN) architectures for multi-modal rigid and affine registration of the CT-MRI images of the brain. A dataset consisting of CT-MRI images of 37 subjects was used for training and evaluation of the networks. For both networks, the proposed models achieved high mutual information value between predicted CT... 

    Minimization of target registration error for vertebra in image-guided spine surgery

    , Article International Journal of Computer Assisted Radiology and Surgery ; Vol. 9, issue. 1 , January , 2014 , p. 29-38 Ershad, M ; Ahmadian, A ; Dadashi Serej, N ; Saberi, H ; Amini Khoiy, K ; Sharif University of Technology
    Purpose: The accuracy of pedicle screw placement during image-guided spine surgery (IGSS) can be characterized by estimating the target registration error (TRE). The major factors that influence TRE were identified, minimized, and verified with in vitro experiments. Materials and methods: Computed-tomography- compatible markers are placed over anatomical landmarks of lumbar vertebral segments in locations that are feasible and routinely used in surgical procedures. TRE was determined directly for markers placed on the pedicles of vertebra segments. First, optimum selections of landmarks are proposed for different landmarks according to the minimum achievable TRE values in different... 

    Nonrigid registration of breast MR images using residual complexity similarity measure

    , Article Iranian Conference on Machine Vision and Image Processing, MVIP, Zanjan ; Sept , 2013 , Pages 241-244 ; 21666776 (ISSN); 9781467361842 (ISBN) Nekoo, A. H ; Ghaffari, A ; Fatemizadeh, E ; Sharif University of Technology
    IEEE Computer Society  2013
    Elimination of motion artifact in breast MR images is a significant issue in pre-processing step before utilizing images for diagnostic applications. Breast MR Images are affected by slow varying intensity distortions as a result of contrast agent enhancement. Thus a nonrigid registration algorithm considering this effect is needed. Traditional similarity measures such as sum of squared differences and cross correlation, ignore the mentioned distortion. Therefore, efficient registration is not obtained. Residual complexity is a similarity measure that considers spatially varying intensity distortions by maximizing sparseness of the residual image. In this research, the results obtained by... 

    A multiscale phase field method for joint segmentation-rigid registration application to motion estimation of human knee joint

    , Article Biomedical Engineering - Applications, Basis and Communications ; Volume 23, Issue 6 , 2011 , Pages 445-456 ; 10162372 (ISSN) Eslami, A ; Esfandiarpour, F ; Shakourirad, A ; Farahmand, F ; Sharif University of Technology
    Image based registration of rigid objects has been frequently addressed in the literature to obtain an object's motion parameters. In this paper, a new approach of joint segmentation-rigid registration, within the variational framework of the phase field approximation of the Mumford-Shah's functional, is proposed. The defined functional consists of two Mumford-Shah equations, extracting the discontinuity set of the reference and target images due to a rigid spatial transformation. Multiscale minimization of the proposed functional after finite element discretization provided a sub-pixel, robust algorithm for edge extraction as well as edge based rigid registration. The implementation...