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  • Open Access


    Deep Learning for Image Segmentation: A Focus on Medical Imaging

    Ali F. Khalifa1, Eman Badr1,2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1995-2024, 2023, DOI:10.32604/cmc.2023.035888

    Abstract Image segmentation is crucial for various research areas. Many computer vision applications depend on segmenting images to understand the scene, such as autonomous driving, surveillance systems, robotics, and medical imaging. With the recent advances in deep learning (DL) and its confounding results in image segmentation, more attention has been drawn to its use in medical image segmentation. This article introduces a survey of the state-of-the-art deep convolution neural network (CNN) models and mechanisms utilized in image segmentation. First, segmentation models are categorized based on their model architecture and primary working principle. Then, CNN categories are described, and various models are… More >

  • Open Access


    Polymers from Renewable Resources: Perspectives in Biomedical Applications

    Andrea Morelli, Dario Puppi, Federica Chiellini*

    Journal of Renewable Materials, Vol.1, No.2, pp. 83-112, 2013, DOI:10.7569/JRM.2012.634106

    Abstract Polymers, particularly those susceptible to undergoing biodegradation under physiological environments, can be considered the materials of choice for biomedical applications such as tissue engineering, regenerative medicine, and controlled and targeted drug delivery. The development of these relatively new fi elds of biomedical research represents the driving force towards the exploitation of renewable resources for the obtainment of biobased polymeric biomaterials. This perspective article reports on the biomedical applications of three major categories of biobased polymeric materials obtained from renewable resources, namely, polysaccharides, proteins and polyesters of natural origins. Particular emphasis is given to biobased polymers that display only minor modifi… More >

  • Open Access


    Pathways for Sustainable Utilization of Waste Chicken Eggshell

    Omojola Awogbemi1,*, Daramy Vandi Von Kallon1, Victor Sunday Aigbodion2,3

    Journal of Renewable Materials, Vol.10, No.8, pp. 2217-2246, 2022, DOI:10.32604/jrm.2022.019152

    Abstract Chicken eggshell is one of the most common wastes generated from households, restaurants and other food processing outlets. Waste Chicken Eggshells (WCES) also constitutes an environmental nuisance and ends up discarded at dumping site with no consideration of further usage. The main constituent of WCES is calcium carbonate from which calcium or calcium oxide can be extracted for various applications. This current effort reviews recently published literature on the diverse applications of WCES. The considered utilization avenues include catalysts for biofuel production, construction industry, wastewater purification, industrial sector, food industry, medical, and agricultural applications. The specific areas of application apart… More > Graphic Abstract

    Pathways for Sustainable Utilization of Waste Chicken Eggshell

  • Open Access


    Fusion Based Tongue Color Image Analysis Model for Biomedical Applications

    Esam A. AlQaralleh1, Halah Nassif2, Bassam A. Y. Alqaralleh2,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5477-5490, 2022, DOI:10.32604/cmc.2022.024364

    Abstract Tongue diagnosis is a novel and non-invasive approach commonly employed to carry out the supplementary diagnosis over the globe. Recently, several deep learning (DL) based tongue color image analysis models have existed in the literature for the effective detection of diseases. This paper presents a fusion of handcrafted with deep features based tongue color image analysis (FHDF-TCIA) technique to biomedical applications. The proposed FDHF-TCIA technique aims to investigate the tongue images using fusion model, and thereby determines the existence of disease. Primarily, the FHDF-TCIA technique comprises Gaussian filtering based preprocessing to eradicate the noise. The proposed FHDF-TCIA model encompasses a… More >

  • Open Access


    Machine Learning Applied to Problem-Solving in Medical Applications

    Mahmoud Ragab1,2, Ali Algarni3, Adel A. Bahaddad4, Romany F. Mansour5,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2277-2294, 2021, DOI:10.32604/cmc.2021.018000

    Abstract Physical health plays an important role in overall well-being of the human beings. It is the most observed dimension of health among others such as social, intellectual, emotional, spiritual and environmental dimensions. Due to exponential increase in the development of wireless communication techniques, Internet of Things (IoT) has effectively penetrated different aspects of human lives. Healthcare is one of the dynamic domains with ever-growing demands which can be met by IoT applications. IoT can be leveraged through several health service offerings such as remote health and monitoring services, aided living, personalized treatment, and so on. In this scenario, Deep Learning… More >

  • Open Access


    Intelligent Autonomous-Robot Control for Medical Applications

    Rihem Farkh1,2, Haykel Marouani1,*, Khaled Al Jaloud1, Saad Alhuwaimel3, Mohammad Tabrez Quasim4, Yasser Fouad1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2189-2203, 2021, DOI:10.32604/cmc.2021.015906

    Abstract The COVID-19 pandemic has shown that there is a lack of healthcare facilities to cope with a pandemic. This has also underscored the immediate need to rapidly develop hospitals capable of dealing with infectious patients and to rapidly change in supply lines to manufacture the prescription goods (including medicines) that is needed to prevent infection and treatment for infected patients. The COVID-19 has shown the utility of intelligent autonomous robots that assist human efforts to combat a pandemic. The artificial intelligence based on neural networks and deep learning can help to fight COVID-19 in many ways, particularly in the control… More >

  • Open Access


    An Application Review of Artificial Intelligence in Prevention and Cure of COVID-19 Pandemic

    Peipeng Yu1, Zhihua Xia1, *, Jianwei Fei1, Sunil Kumar Jha1, 2

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 743-760, 2020, DOI:10.32604/cmc.2020.011391

    Abstract Coronaviruses are a well-known family of viruses that can infect humans or animals. Recently, the new coronavirus (COVID-19) has spread worldwide. All countries in the world are working hard to control the coronavirus disease. However, many countries are faced with a lack of medical equipment and an insufficient number of medical personnel because of the limitations of the medical system, which leads to the mass spread of diseases. As a powerful tool, artificial intelligence (AI) has been successfully applied to solve various complex problems ranging from big data analysis to computer vision. In the process of epidemic control, many algorithms… More >

  • Open Access


    The Identification of Elastic Moduli of a Stratified Layer Through Localized Surface Probes, with Biomedical Applications

    A.R.Skovoroda1, R.V.Goldstein2

    CMES-Computer Modeling in Engineering & Sciences, Vol.4, No.3&4, pp. 457-472, 2003, DOI:10.3970/cmes.2003.004.457

    Abstract We discuss the inverse problem of the recovery of the distribution of the elastic moduli of a stratified layer, based on measurements of the surface displacement under localized surface loads. A general parametric solution and a numerical procedure for computing the parameters are presented. Examples of numerical results are given. The problem and its solution are related to the monitoring of elastic properties of living tissues. More >

  • Open Access


    Structural Refinement of Titanium-Aluminum-Niobium Alloy for Biomedical Applications

    Joaquín E. González-Hernández1, Jorge M. Cubero-Sesin1,2*, Elena Ulate-Kolitsky1, Priscilla Navarro1, Stephen Petretti1, Zenji Horita3,4

    Journal of Renewable Materials, Vol.5, No.3-4, pp. 300-306, 2017, DOI:10.7569/JRM.2017.634120

    Abstract In this work, a modification of the microstructure of a commercial Ti-6Al-7Nb alloy was accomplished by high-pressure torsion (HPT) at room temperature, to produce a bulk nanostructure on discs of 10 mm diameter and ~0.8 mm thickness. The metallographic analyses of the discs were performed by optical microscopy and scanning electron microscopy with energy dispersive spectroscopy. The results confirmed the presence of aluminum (Al) and niobium (Nb) as the sole alloying elements, promoting a duplex (α + β) titanium (Ti) microstructure prior to HPT processing. After HPT processing, nanostructure refinement was attained, reflected in the X-ray diffraction profiles as broadening… More >

  • Open Access


    Functional Electrospun Poly (Lactic Acid) Scaffolds for Biomedical Applications: Experimental Conditions, Degradation and Biocompatibility Study

    Idalba A. Hidalgo A., Felipe Sojo, Francisco Arvelo, Marcos A. Sabino∗,‡

    Molecular & Cellular Biomechanics, Vol.10, No.2, pp. 85-105, 2013, DOI:10.3970/mcb.2013.010.085

    Abstract The electrospinning technique is a method used to produce nano and microfibers using the influence of electrostatic forces. Porous three dimensional networks of continuous and interconnected fibers as scaffolds were obtained from a poly (lactic acid) solution. The concentration of the polymeric solution, 12.5% m/w, as well as the conditions of voltage (V=11kV) and tip-metallic collector distance (H=13cm) were established to develop these scaffolds through the electrospinning process. The characteristics of the scaffolds, such as fiber diameter, sintering and the biomimetics of the characteristics of a native extra cellular matrix were verified by Scanning Electron Microscopy (SEM). The orientation induced… More >

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