Liuqiang Shu, Lei Yu*
CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 627-644, 2025, DOI:10.32604/cmc.2024.056077
- 03 January 2025
Abstract Bone age assessment (BAA) aims to determine whether a child’s growth and development are normal concerning their chronological age. To predict bone age more accurately based on radiographs, and for the left-hand X-ray images of different races model can have better adaptability, we propose a neural network in parallel with the quantitative features from the left-hand bone measurements for BAA. In this study, a lightweight feature extractor (LFE) is designed to obtain the feature maps from radiographs, and a module called attention eraser module (AEM) is proposed to capture the fine-grained features. Meanwhile, the dimensional… More >
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