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  • Open Access

    ARTICLE

    A Semantic Adversarial Network for Detection and Classification of Myopic Maculopathy

    Qaisar Abbas1, Abdul Rauf Baig1,*, Ayyaz Hussain2

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1483-1499, 2023, DOI:10.32604/cmc.2023.036366 - 06 February 2023

    Abstract The diagnosis of eye disease through deep learning (DL) technology is the latest trend in the field of artificial intelligence (AI). Especially in diagnosing pathologic myopia (PM) lesions, the implementation of DL is a difficult task because of the classification complexity and definition system of PM. However, it is possible to design an AI-based technique that can identify PM automatically and help doctors make relevant decisions. To achieve this objective, it is important to have adequate resources such as a high-quality PM image dataset and an expert team. The primary aim of this research is… More >

  • Open Access

    ARTICLE

    Detection of Diabetic Retinopathy from Retinal Images Using DenseNet Models

    R. Nandakumar1, P. Saranya2,*, Vijayakumar Ponnusamy3, Subhashree Hazra2, Antara Gupta2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 279-292, 2023, DOI:10.32604/csse.2023.028703 - 16 August 2022

    Abstract A prevalent diabetic complication is Diabetic Retinopathy (DR), which can damage the retina’s veins, leading to a severe loss of vision. If treated in the early stage, it can help to prevent vision loss. But since its diagnosis takes time and there is a shortage of ophthalmologists, patients suffer vision loss even before diagnosis. Hence, early detection of DR is the necessity of the time. The primary purpose of the work is to apply the data fusion/feature fusion technique, which combines more than one relevant feature to predict diabetic retinopathy at an early stage with… More >

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