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  • Open Access

    ARTICLE

    Enhancing Ulcerative Colitis Diagnosis: A Multi-Level Classification Approach with Deep Learning

    Hasan J. Alyamani*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1129-1142, 2024, DOI:10.32604/cmes.2024.047756 - 16 April 2024

    Abstract The evaluation of disease severity through endoscopy is pivotal in managing patients with ulcerative colitis, a condition with significant clinical implications. However, endoscopic assessment is susceptible to inherent variations, both within and between observers, compromising the reliability of individual evaluations. This study addresses this challenge by harnessing deep learning to develop a robust model capable of discerning discrete levels of endoscopic disease severity. To initiate this endeavor, a multi-faceted approach is embarked upon. The dataset is meticulously preprocessed, enhancing the quality and discriminative features of the images through contrast limited adaptive histogram equalization (CLAHE). A More > Graphic Abstract

    Enhancing Ulcerative Colitis Diagnosis: A Multi-Level Classification Approach with Deep Learning

  • Open Access

    ARTICLE

    Two-Fold and Symmetric Repeatability Rates for Comparing Keypoint Detectors

    Ibrahim El rube'*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6495-6511, 2022, DOI:10.32604/cmc.2022.031602 - 28 July 2022

    Abstract The repeatability rate is an important measure for evaluating and comparing the performance of keypoint detectors. Several repeatability rate measurements were used in the literature to assess the effectiveness of keypoint detectors. While these repeatability rates are calculated for pairs of images, the general assumption is that the reference image is often known and unchanging compared to other images in the same dataset. So, these rates are asymmetrical as they require calculations in only one direction. In addition, the image domain in which these computations take place substantially affects their values. The presented scatter diagram… More >

  • Open Access

    ARTICLE

    From Geometric Transformations to Auxetic Metamaterials

    Ligia Munteanu1, Veturia Chiroiu1, Viorel Şerban2

    CMC-Computers, Materials & Continua, Vol.42, No.3, pp. 175-204, 2014, DOI:10.3970/cmc.2014.042.175

    Abstract The paper introduces a new alternative towards fabrication of auxetic metamaterials (materials with negative Poisson’s ratio) controlled by geometric transformations. These transformations are derived from the theory of small (infinitesimal) elastic deformation superimposed on finite elastic deformations. By using this theory, a cylindrical region filled with initial deformed foam is transformed through deformation into a cylindrical shell region filled with auxetic metamaterial. As an example, the realization of the seismic cloak device becomes a practical possibility. More >

  • Open Access

    ARTICLE

    On the Compression Viewed as a Geometric Transformation

    Ligia Munteanu1, Cornel Brisan2, Veturia Chiroiu3, Stefania Donescu4

    CMC-Computers, Materials & Continua, Vol.31, No.2, pp. 127-146, 2012, DOI:10.3970/cmc.2012.031.127

    Abstract A modeling of the compression by using the property of Helmholtz equation to be invariant under geometric transformations is presented in this paper. The versatility of the geometric transformations is illustrated in order to obtain a new interpretation of the compression process. The physical spatial compression leads, most of the times, to new materials with inhomogeneous and anisotropic properties. The compression can be theoretically controlled by the geometric transformations. As an example, new architectures for auxetic materials can be built up by applying the geometric transformations. The new versions are finding their full correspondents in More >

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