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  • Open Access

    ARTICLE

    Significant Changes in Morphological Traits of 422 Barley (Hordeum vulgare L.) Varieties with Different Registration

    Valentina Spanic1,*, Zvonimir Lalic2, Ivica Berakovic1, Luka Drenjancevic2, Goran Jukic2, Ivan Varnica2

    Phyton-International Journal of Experimental Botany, Vol.94, No.2, pp. 317-330, 2025, DOI:10.32604/phyton.2025.058201 - 06 March 2025

    Abstract Enhanced grain yield is achieved in barley by developing varieties incorporating grain yield-related and morphological traits derived from different varieties. The evaluation of 28 morphological characteristics of 422 barley varieties was carried out to assess their changes over time from 1973 to 2023. Most barley yield improvement seems to have been achieved by changes in morphological traits where modern varieties out-yielded older varieties for more than 30% (from 1973 to 2023). According to the Pareto chart, the length of the first segment of the rachis was found to be the most important parameter that changed… More >

  • Open Access

    ARTICLE

    GAN-DIRNet: A Novel Deformable Image Registration Approach for Multimodal Histological Images

    Haiyue Li1, Jing Xie2, Jing Ke3, Ye Yuan1, Xiaoyong Pan1, Hongyi Xin4, Hongbin Shen1,*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 487-506, 2024, DOI:10.32604/cmc.2024.049640 - 18 July 2024

    Abstract Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue. Convolutional neural network (CNN) and generative adversarial network (GAN) are pivotal in medical image registration. However, existing methods often struggle with severe interference and deformation, as seen in histological images of conditions like Cushing’s disease. We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator in GAN. In this study, we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration. To… More >

  • Open Access

    ARTICLE

    Direct Pointwise Comparison of FE Predictions to StereoDIC Measurements: Developments and Validation Using Double Edge-Notched Tensile Specimen

    Troy Myers1, Michael A. Sutton1,*, Hubert Schreier2, Alistair Tofts2, Sreehari Rajan Kattil1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1263-1298, 2024, DOI:10.32604/cmes.2024.048743 - 20 May 2024

    Abstract To compare finite element analysis (FEA) predictions and stereovision digital image correlation (StereoDIC) strain measurements at the same spatial positions throughout a region of interest, a field comparison procedure is developed. The procedure includes (a) conversion of the finite element data into a triangular mesh, (b) selection of a common coordinate system, (c) determination of the rigid body transformation to place both measurements and FEA data in the same system and (d) interpolation of the FEA nodal information to the same spatial locations as the StereoDIC measurements using barycentric coordinates. For an aluminum Al-6061 double edge More >

  • Open Access

    ARTICLE

    Nonlinear Registration of Brain Magnetic Resonance Images with Cross Constraints of Intensity and Structure

    Han Zhou1,2, Hongtao Xu1,2, Xinyue Chang1,2, Wei Zhang1,2, Heng Dong1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2295-2313, 2024, DOI:10.32604/cmc.2024.047754 - 15 May 2024

    Abstract Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes. However, these methods often lack constraint information and overlook semantic consistency, limiting their performance. To address these issues, we present a novel approach for medical image registration called the Dual-VoxelMorph, featuring a dual-channel cross-constraint network. This innovative network utilizes both intensity and segmentation images, which share identical semantic information and feature representations. Two encoder-decoder structures calculate deformation fields for intensity and segmentation images, as generated by the dual-channel cross-constraint network. This design facilitates bidirectional communication between grayscale More >

  • Open Access

    ARTICLE

    A Novel Unsupervised MRI Synthetic CT Image Generation Framework with Registration Network

    Liwei Deng1, Henan Sun1, Jing Wang2, Sijuan Huang3, Xin Yang3,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2271-2287, 2023, DOI:10.32604/cmc.2023.039062 - 29 November 2023

    Abstract In recent years, radiotherapy based only on Magnetic Resonance (MR) images has become a hot spot for radiotherapy planning research in the current medical field. However, functional computed tomography (CT) is still needed for dose calculation in the clinic. Recent deep-learning approaches to synthesized CT images from MR images have raised much research interest, making radiotherapy based only on MR images possible. In this paper, we proposed a novel unsupervised image synthesis framework with registration networks. This paper aims to enforce the constraints between the reconstructed image and the input image by registering the reconstructed… More >

  • Open Access

    ARTICLE

    Automatic Extraction of the Sparse Prior Correspondences for Non-Rigid Point Cloud Registration

    Yan Zhu1,2, Lili Tian2, Fan Ye2, Gaofeng Sun1, Xianyong Fang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1835-1856, 2023, DOI:10.32604/cmes.2023.025662 - 06 February 2023

    Abstract Non-rigid registration of point clouds is still far from stable, especially for the largely deformed one. Sparse initial correspondences are often adopted to facilitate the process. However, there are few studies on how to build them automatically. Therefore, in this paper, we propose a robust method to compute such priors automatically, where a global and local combined strategy is adopted. These priors in different degrees of deformation are obtained by the locally geometrical-consistent point matches from the globally structural-consistent region correspondences. To further utilize the matches, this paper also proposes a novel registration method based More >

  • Open Access

    ARTICLE

    Secure Key Management Based Mobile Authentication in Cloud

    S. Shanmuga Priya1, D. Yuvaraj2,*, T. Satyanarayana Murthy3, Varghese S. Chooralil4, S. Navaneetha Krishnan5, P. Banumathy6, P. SundaraVadivel7

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 887-896, 2022, DOI:10.32604/csse.2022.021845 - 09 May 2022

    Abstract Authentication is important to the security of user data in a mobile cloud environment. Because of the server’s user credentials, it is subject to attacks. To maintain data authentication, a novel authentication mechanism is proposed. It consists of three independent phases: Registration, login, and authentication and key agreement. The user registers with the Registration Center (RC) by producing a secret number that isn’t stored in the phone, which protects against privileged insider attacks. The user and server generate a nonce for dynamic user identity and agree on a session secret key for safe communication. The… More >

  • Open Access

    ARTICLE

    Optical Flow with Learning Feature for Deformable Medical Image Registration

    Jinrong Hu1, Lujin Li1, Ying Fu1, Maoyang Zou1, Jiliu Zhou1, Shanhui Sun2,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2773-2788, 2022, DOI:10.32604/cmc.2022.017916 - 07 December 2021

    Abstract Deformable medical image registration plays a vital role in medical image applications, such as placing different temporal images at the same time point or different modality images into the same coordinate system. Various strategies have been developed to satisfy the increasing needs of deformable medical image registration. One popular registration method is estimating the displacement field by computing the optical flow between two images. The motion field (flow field) is computed based on either gray-value or handcrafted descriptors such as the scale-invariant feature transform (SIFT). These methods assume that illumination is constant between images. However,… More >

  • Open Access

    ARTICLE

    Attention-Based and Time Series Models for Short-Term Forecasting of COVID-19 Spread

    Jurgita Markevičiūtė1,*, Jolita Bernatavičienė2, Rūta Levulienė1, Viktor Medvedev2, Povilas Treigys2, Julius Venskus2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 695-714, 2022, DOI:10.32604/cmc.2022.018735 - 07 September 2021

    Abstract The growing number of COVID-19 cases puts pressure on healthcare services and public institutions worldwide. The pandemic has brought much uncertainty to the global economy and the situation in general. Forecasting methods and modeling techniques are important tools for governments to manage critical situations caused by pandemics, which have negative impact on public health. The main purpose of this study is to obtain short-term forecasts of disease epidemiology that could be useful for policymakers and public institutions to make necessary short-term decisions. To evaluate the effectiveness of the proposed attention-based method combining certain data mining… More >

  • Open Access

    ARTICLE

    Research on Tracking and Registration Algorithm Based on Natural Feature Point

    Tingting Yang1,*, Shuwen Jia1, Boxiong Yang1, Chenxi Kan2

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 683-692, 2021, DOI:10.32604/iasc.2021.017235 - 20 April 2021

    Abstract In the augmented reality system, the position and direction of the user’s point of view and line of sight in the real scene is acquired in real-time. The position and direction information will determine the exact position of the virtual object of the real scene. At the same time, various coordinate systems are established according to the user’s line of sight. So registration tracking technology is very important. The paper proposes an accurate, stable, and effective augmented reality registration algorithm. The method adopts the method of ORB (oriented FAST and rotated BRIEF) features matching combined More >

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