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  • Open Access


    Liver Tumor Decision Support System on Human Magnetic Resonance Images: A Comparative Study

    Hiam Alquran1,2, Yazan Al-Issa3, Mohammed Alslatie4, Isam Abu-Qasmieh1, Amin Alqudah3, Wan Azani Mustafa5,7,*, Yasmin Mohd Yacob6,7

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1653-1671, 2023, DOI:10.32604/csse.2023.033861

    Abstract Liver cancer is the second leading cause of cancer death worldwide. Early tumor detection may help identify suitable treatment and increase the survival rate. Medical imaging is a non-invasive tool that can help uncover abnormalities in human organs. Magnetic Resonance Imaging (MRI), in particular, uses magnetic fields and radio waves to differentiate internal human organs tissue. However, the interpretation of medical images requires the subjective expertise of a radiologist and oncologist. Thus, building an automated diagnosis computer-based system can help specialists reduce incorrect diagnoses. This paper proposes a hybrid automated system to compare the performance… More >

  • Open Access


    Aggregate Point Cloud Geometric Features for Processing

    Yinghao Li1,2,3, Renbo Xia1,2,*, Jibin Zhao1,2,*, Yueling Chen1,2, Liming Tao1,2,3, Hangbo Zou1,2,3, Tao Zhang1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 555-571, 2023, DOI:10.32604/cmes.2023.024470

    Abstract As 3D acquisition technology develops and 3D sensors become increasingly affordable, large quantities of 3D point cloud data are emerging. How to effectively learn and extract the geometric features from these point clouds has become an urgent problem to be solved. The point cloud geometric information is hidden in disordered, unstructured points, making point cloud analysis a very challenging problem. To address this problem, we propose a novel network framework, called Tree Graph Network (TGNet), which can sample, group, and aggregate local geometric features. Specifically, we construct a Tree Graph by explicit rules, which consists More >

  • Open Access


    A Deep Learning Approach to Mesh Segmentation

    Abubakar Sulaiman Gezawa1, Qicong Wang1,2, Haruna Chiroma3, Yunqi Lei1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1745-1763, 2023, DOI:10.32604/cmes.2022.021351

    Abstract In the shape analysis community, decomposing a 3D shape into meaningful parts has become a topic of interest. 3D model segmentation is largely used in tasks such as shape deformation, shape partial matching, skeleton extraction, shape correspondence, shape annotation and texture mapping. Numerous approaches have attempted to provide better segmentation solutions; however, the majority of the previous techniques used handcrafted features, which are usually focused on a particular attribute of 3D objects and so are difficult to generalize. In this paper, we propose a three-stage approach for using Multi-view recurrent neural network to automatically segment… More > Graphic Abstract

    A Deep Learning Approach to Mesh Segmentation

  • Open Access


    Accurate, High-Speed, Full-Color and Vibration-Resistant 3D Shape Measurement Using Linear LED Devices

    Motoharu Fujigaki1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.23, No.1, pp. 26-26, 2021, DOI:10.32604/icces.2021.08385

    Abstract Several types of accurate and high-speed 3D shape measurement using linear LED devices were developed by author's research group. The linear LED device is a key device to develop them. High-speed phase shift synchronized with camera triggers can be achieved by switching the lighting position of the linear LED. The control signals can be generated easily with a no special micro-computer. A compact projector unit can be produced. Author also proposed a calibration method, named a whole-space tabulation method (WSTM), for an accurate and high-speed shape measurement using multiple reference planes. A handy, fullcolor and… More >

  • Open Access


    The Reproducing Kernel DMS-FEM: 3D Shape Functions and Applications to Linear Solid Mechanics

    Sunilkumar N1, D Roy1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.66, No.3, pp. 249-284, 2010, DOI:10.3970/cmes.2010.066.249

    Abstract We propose a family of 3D versions of a smooth finite element method (Sunilkumar and Roy 2010), wherein the globally smooth shape functions are derivable through the condition of polynomial reproduction with the tetrahedral B-splines (DMS-splines) or tensor-product forms of triangular B-splines and 1D NURBS bases acting as the kernel functions. While the domain decomposition is accomplished through tetrahedral or triangular prism elements, an additional requirement here is an appropriate generation of knotclouds around the element vertices or corners. The possibility of sensitive dependence of numerical solutions to the placements of knotclouds is largely arrested… More >

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