Haiyue Li¹, Jing Xie², Jing Ke³, Ye Yuan¹, Xiaoyong Pan¹, Hongyi Xin⁴, Hongbin Shen^1,*

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 >

Troy Myers¹, Michael A. Sutton^1,*, 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 >

Han Zhou^1,2, Hongtao Xu^1,2, Xinyue Chang^1,2, Wei Zhang^1,2, Heng Dong^1,2,*

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 >

Liwei Deng¹, Henan Sun¹, Jing Wang², Sijuan Huang³, Xin Yang^3,*

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 >

Yan Zhu^1,2, Lili Tian², Fan Ye², Gaofeng Sun¹, Xianyong Fang^2,*

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 >

S. Shanmuga Priya¹, D. Yuvaraj^2,*, 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 >

Jinrong Hu¹, Lujin Li¹, Ying Fu¹, Maoyang Zou¹, Jiliu Zhou¹, Shanhui Sun^2,*

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 >

Jurgita Markevičiūtė^1,*, 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 >

Tingting Yang^1,*, 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 >

Kanwal Imran^1,*, Nasreen Anjum³, Saeed Mahfooz¹, Muhammad Zubair², Zhahoui Yang³, Abdul Haseeb Malik¹, Qazi Ejaz Ali¹, Madeeha Aman¹

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2329-2347, 2021, DOI:10.32604/cmc.2021.017177 - 13 April 2021

Abstract IPv6 over Low Power Wireless Personal Area Network (6LoWPAN) connects the highly constrained sensor nodes with the internet using the IPv6 protocol. 6LoWPAN has improved the scalability of the Internet of Things (IoTs) infrastructure and allows mobile nodes to send packets over the IEEE 802.15.4 wireless network. Several mobility managements schemes have been suggested for handling the registration and handover procedures in 6LoWPAN. However, these schemes have performance constraints, such as increased transmission cost, signalling overhead, registration, and handover latency. To address these issues, we propose a novel cluster-based group mobility scheme (CGM6) for 6LoWPAN.… More >