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  • Open Access

    ARTICLE

    A Novel Convolutional Neural Network Model for Malaria Cell Images Classification

    Esraa Hassan1,3,*, Mahmoud Y. Shams1, Noha A. Hikal2, Samir Elmougy3

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5889-5907, 2022, DOI:10.32604/cmc.2022.025629

    Abstract Infectious diseases are an imminent danger that faces human beings around the world. Malaria is considered a highly contagious disease. The diagnosis of various diseases, including malaria, was performed manually, but it required a lot of time and had some human errors. Therefore, there is a need to investigate an efficient and fast automatic diagnosis system. Deploying deep learning algorithms can provide a solution in which they can learn complex image patterns and have a rapid improvement in medical image analysis. This study proposed a Convolutional Neural Network (CNN) model to detect malaria automatically. A Malaria Convolutional Neural Network (MCNN)… More >

  • Open Access

    ARTICLE

    A Morphological Image Segmentation Algorithm for Circular Overlapping Cells

    Fuchu Zhang1, Yanpeng Wu2,*, Miaoqing Xu2, Sanjun Liu3, Changling Peng2, Zhichen Gao4

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 301-321, 2022, DOI:10.32604/iasc.2022.021929

    Abstract Cell segmentation is an important topic in medicine. A cell image segmentation algorithm based on morphology is proposed. First, some morphological operations, including top-hat transformation, bot-hat transformation, erosion operation, dilation operation, opening operation, closing operation, majority operation, skeleton operation, etc., are applied to remove noise or enhance cell images. Then the small blocks in the cell image are deleted as noise, the medium blocks are removed and saved as normal cells, and the large blocks are segmented as overlapping cells. Each point on the edge of the overlapping cell area to be divided is careful checked. If the shape of… More >

  • Open Access

    REVIEW

    A Narrative Review: Classification of Pap Smear Cell Image for Cervical Cancer Diagnosis

    Wan Azani Mustafa1,*, Afiqah Halim1, Khairul Shakir Ab Rahman2

    Oncologie, Vol.22, No.2, pp. 53-63, 2020, DOI:10.32604/oncologie.2020.013660

    Abstract Cervical cancer develops as cells transformation in the cervix of a female that connects the uterus to the vagina. This cancer may impact the columnal epithelial cells of the cervix and therefore can be expanded to the lymphatic and circulatory system (metastasize), sometimes the kidneys, liver, prostate, vagina, and rectum. Many of the cervical cancer patients survived by taking early prevention by undergoing a Pap Smear Test. However, the result of the test usually takes a few weeks which is extremely time-consuming especially at the government hospital. The purpose of this research was to study the detection and classification method… More >

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