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  • Open Access

    ARTICLE

    Application of Dual Modality Contrast Agent Combined with Multi-Scale Representation in Ultrasound-Magnetic Resonance Imaging Registration Scheme

    Mo Hou1,*, Weiyu Kevin Chiang2,*, Weiqiang Hong1, Maoyun Yang1, Wenhua Yu3,4

    Molecular & Cellular Biomechanics, Vol.17, No.4, pp. 165-178, 2020, DOI:10.32604/mcb.2020.010805

    Abstract To achieve the image registration/fusion and perfect the quality of the integration, with dual modality contrast agent (DMCA), a novel multi-scale representation registration method between ultrasound imaging (US) and magnetic resonance imaging (MRI) is presented in the paper, and how DMCA influence on registration accuracy is chiefly discussed. Owing to US’s intense speckle noise, it is a tremendous challenge to register US with any other modality images. How to improve the algorithms for US processing has become the bottleneck, and in the short term it is difficult to have a breakthrough. In that case, DMCA is employed in both US… More >

  • Open Access

    ARTICLE

    Who Will Come: Predicting Freshman Registration Based on Decision Tree

    Lei Yang1, Li Feng1, *, Liwei Tian1, Hongning Dai1

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1825-1836, 2020, DOI:10.32604/cmc.2020.010011

    Abstract The registration rate of freshmen has been a great concern at many colleges and universities, particularly private institutions. Traditionally, there are two inquiry methods: telephone and tuition-payment-status. Unfortunately, the former is not only time-consuming but also suffers from the fact that many students tend to keep their choices secret. On the other hand, the latter is not always feasible because only few students are willing to pay their university tuition fees in advance. It is often believed that it is impossible to predict incoming freshmen’s choice of university due to the large amount of subjectivity. However, if we look at… More >

  • Open Access

    ARTICLE

    Hierarchical Rigid Registration of Femur Surface Model Based on Anatomical Features

    Xiaozhong Chen*

    Molecular & Cellular Biomechanics, Vol.17, No.3, pp. 139-153, 2020, DOI:10.32604/mcb.2020.08933

    Abstract Existing model registration of individual bones does not have a high certainly of success due to the lack of anatomic semantic. In light of the surface anatomy and functional structure of bones, we hypothesized individual femur models would be aligned through feature points both in geometrical level and in anatomic level, and proposed a hierarchical approach for the rigid registration (HRR) of point cloud models of femur with high resolution. Firstly, a coarse registration between two simplified point cloud models was implemented based on the extraction of geometric feature points (GFPs); and then, according to the anatomic feature points (AFPs)… More >

  • Open Access

    ARTICLE

    Optical-CT Dual-Modality Mapping Base on DRR Registration

    Qingyang Zang1, Dongsheng Li1, Chunxiao Chen1,*, Jianfei Li1

    Molecular & Cellular Biomechanics, Vol.16, No.4, pp. 253-263, 2019, DOI:10.32604/mcb.2019.06999

    Abstract Optical-CT dual-modality imaging requires the mapping between 2D fluorescence images and 3D body surface light flux. In this paper, we proposed an optical-CT dual-modality image mapping algorithm based on the Digitally Reconstructed Radiography (DRR) registration. In the process of registration, a series of DRR images were computed from CT data using the ray casting algorithm. Then, the improved HMNI similarity strategy based on Hausdorff distance was used to complete the registration of the white-light optical images and DRR virtual images. According to the corresponding relationship obtained by the image registration and the Lambert’s cosine law based on the pin-hole imaging… More >

  • Open Access

    ABSTRACT

    Image registration procedure used in intrasubject comparison of pelvic configuration

    P. Ruzicka1, P. Bendova1, S. Konvickova1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.10, No.3, pp. 91-96, 2009, DOI:10.3970/icces.2009.010.091

    Abstract The objective of the study was to prove magnetic resonance imaging as suitable instrument for exploring the nature and amplitude of displacements within the bony pelvis induced by asymmetrically altered pelvic floor muscle characteristics. Repeated MR imaging of 14 females was performed. Spatial coordinates of 23 pelvic landmarks were localized in each subject and registered by interactive and automatic procedures. Modalities of registration procedure were tested and compared by the precision of registration. The software tool was developed to perform registrations and data analyses including individual registration error evaluation. The automatic registration with vertebra L5 as reference has been found… More >

  • Open Access

    ARTICLE

    Dynamic Lung Modeling and Tumor Tracking Using Deformable Image Registration and Geometric Smoothing

    Yongjie Zhang, Yiming Jing, Xinghua Liang, Guoliang Xu, Lei Dong

    Molecular & Cellular Biomechanics, Vol.9, No.3, pp. 213-226, 2012, DOI:10.3970/mcb.2012.009.213

    Abstract A greyscale-based fully automatic deformable image registration algorithm, based on an optical flow method together with geometric smoothing, is developed for dynamic lung modeling and tumor tracking. In our computational processing pipeline, the input data is a set of 4D CT images with 10 phases. The triangle mesh of the lung model is directly extracted from the more stable exhale phase (Phase 5). In addition, we represent the lung surface model in 3D volumetric format by applying a signed distance function and then generate tetrahedral meshes. Our registration algorithm works for both triangle and tetrahedral meshes. In CT images, the… More >

  • Open Access

    ARTICLE

    Rigid Medical Image Registration Using Learning-Based Interest Points and Features

    Maoyang Zou1,2, Jinrong Hu2, Huan Zhang2, Xi Wu2, Jia He2, Zhijie Xu3, Yong Zhong1,*

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 511-525, 2019, DOI:10.32604/cmc.2019.05912

    Abstract For image-guided radiation therapy, radiosurgery, minimally invasive surgery, endoscopy and interventional radiology, one of the important techniques is medical image registration. In our study, we propose a learning-based approach named “FIP-CNNF” for rigid registration of medical image. Firstly, the pixel-level interest points are computed by the full convolution network (FCN) with self-supervise. Secondly, feature detection, descriptor and matching are trained by convolution neural network (CNN). Thirdly, random sample consensus (Ransac) is used to filter outliers, and the transformation parameters are found with the most inliers by iteratively fitting transforms. In addition, we propose “TrFIP-CNNF” which uses transfer learning and fine-tuning… More >

  • Open Access

    ARTICLE

    Real-Time Moving Targets Detection in Dynamic Scenes

    Fan Li1, Yang Yang

    CMES-Computer Modeling in Engineering & Sciences, Vol.107, No.2, pp. 103-124, 2015, DOI:10.3970/cmes.2015.107.103

    Abstract The shift of the camera leads to unsteadiness of backgrounds in video sequences. The motion of camera will results in mixture of backgrounds and foregrounds motion. So it is a challenge for targets detection in dynamic scenes. A realtime moving target detection algorithm with low complexity in dynamic scenes is proposed in this paper. Sub-block based image registration is applied to remove the global motion of the video frame. Considering the blocks in one frame have different motion vectors, the global motion of each block is separately estimated. Then, a neighbor-based background modeling is applied to extract the moving objects.… More >

  • Open Access

    ARTICLE

    Matching Contours in Images through the use of Curvature, Distance to Centroid and Global Optimization with Order-Preserving Constraint

    Francisco P. M. Oliveira1, João Manuel R. S. Tavares1

    CMES-Computer Modeling in Engineering & Sciences, Vol.43, No.1, pp. 91-110, 2009, DOI:10.3970/cmes.2009.043.091

    Abstract This paper presents a new methodology to establish the best global match of objects' contours in images. The first step is the extraction of the sets of ordered points that define the objects' contours. Then, by using the curvature value and its distance to the corresponded centroid for each point, an affinity matrix is built. This matrix contains information of the cost for all possible matches between the two sets of ordered points. Then, to determine the desired one-to-one global matching, an assignment algorithm based on dynamic programming is used. This algorithm establishes the global matching of the minimum global… More >

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