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  • Open Access

    ARTICLE

    Non Sub-Sampled Contourlet with Joint Sparse Representation Based Medical Image Fusion

    Kandasamy Kittusamy*, Latha Shanmuga Vadivu Sampath Kumar

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1989-2005, 2023, DOI:10.32604/csse.2023.026501

    Abstract Medical Image Fusion is the synthesizing technology for fusing multimodal medical information using mathematical procedures to generate better visual on the image content and high-quality image output. Medical image fusion represents an indispensible role in fixing major solutions for the complicated medical predicaments, while the recent research results have an enhanced affinity towards the preservation of medical image details, leaving color distortion and halo artifacts to remain unaddressed. This paper proposes a novel method of fusing Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) using a hybrid model of Non Sub-sampled Contourlet Transform (NSCT) and Joint Sparse Representation (JSR). This… More >

  • Open Access

    ARTICLE

    Hybrid Optimized Learning for Lung Cancer Classification

    R. Vidhya1,*, T. T. Mirnalinee2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 911-925, 2022, DOI:10.32604/iasc.2022.025060

    Abstract Computer tomography (CT) scan images can provide more helpful diagnosis information regarding the lung cancers. Many machine learning and deep learning algorithms are formulated using CT input scan images for the improvisation in diagnosis and treatment process. But, designing an accurate and intelligent system still remains in darker side of the research side. This paper proposes the novel classification model which works on the principle of fused features and optimized learning network. The proposed framework incorporates the principle of saliency maps as a first tier segmentation, which is then fused with deep convolutional neural networks to improve the classification maps… More >

  • Open Access

    ARTICLE

    Oil Production Optimization by Means of a Combined “Plugging, Profile Control, and Flooding” Treatment: Analysis of Results Obtained Using Computer Tomography and Nuclear Magnetic Resonance

    Yanyue Li1, Changlong Liu1, Wenbo Bao1,*, Baoqing Xue1, Peng Lv1, Nan Wang1, Hui Li1, Wenguo Ma2

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.3, pp. 737-749, 2022, DOI:10.32604/fdmp.2022.019139

    Abstract

    Due to long-term water injection, often oilfields enter the so-called medium and high water cut stage, and it is difficult to achieve good oil recovery and water reduction through standard methods (single profile control and flooding measures). Therefore, in this study, a novel method based on “plugging, profile control, and flooding” being implemented at the same time is proposed. To assess the performances of this approach, physical simulations, computer tomography, and nuclear magnetic resonance are used. The results show that the combination of a gel plugging agent, a polymer microsphere flooding agent, and a high-efficiency oil displacement agent leads to… More >

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