Pediatric Bone Age Assessment using Deep Learning Models

Aravinda Raman, Sameena Pathan, Tanweer Ali
7/20/2022
eess.IVcs.CVcs.LG

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Abstract

Bone age assessment (BAA) is a standard method for determining the age difference between skeletal and chronological age. Manual processes are complicated and necessitate the expertise of experts. This is where deep learning comes into play. In this study, pre-trained models like VGG-16, InceptionV3, XceptionNet, and MobileNet are used to assess the bone age of the input data, and their mean average errors are compared and evaluated to see which model predicts the best.

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Cite this paper

@article{raman2022pediatric,
  title  = {Pediatric Bone Age Assessment using Deep Learning Models},
  author = {Aravinda Raman and Sameena Pathan and Tanweer Ali},
  year   = {2022},
  eprint = {2207.10169},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2207.10169v1}
}

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