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    Metaheuristic with Deep Learning Enabled Biomedical Bone Age Assessment and Classification Model

    Mesfer Al Duhayyim1,*, Areej A. Malibari2, Marwa Obayya3, Mohamed K. Nour4, Ahmed S. Salama5, Mohamed I. Eldesouki6, Abu Sarwar Zamani7, Mohammed Rizwanullah7

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5473-5489, 2022, DOI:10.32604/cmc.2022.031976

    Abstract The skeletal bone age assessment (BAA) was extremely implemented in development prediction and auxiliary analysis of medicinal issues. X-ray images of hands were detected from the estimation of bone age, whereas the ossification centers of epiphysis and carpal bones are important regions. The typical skeletal BAA approaches remove these regions for predicting the bone age, however, few of them attain suitable efficacy or accuracy. Automatic BAA techniques with deep learning (DL) methods are reached the leading efficiency on manual and typical approaches. Therefore, this study introduces an intellectual skeletal bone age assessment and classification with the use of metaheuristic with… More >

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