Deep learning-based automated bone age estimation for Saudi patients on hand radiograph images: a retrospective study
Zuhal Y. Hamd,
Amal I. Alorainy,
Mohammed A. Alharbi
et al.
Abstract:Purpose
In pediatric medicine, precise estimation of bone age is essential for skeletal maturity evaluation, growth disorder diagnosis, and therapeutic intervention planning. Conventional techniques for determining bone age depend on radiologists’ subjective judgments, which may lead to non-negligible differences in the estimated bone age. This study proposes a deep learning-based model utilizing a fully connected convolutional neural network(CNN) to predict bone age from left-hand radiographs.
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