Paediatric Bone Age Assessment from Hand X-ray Using Deep Learning Approach-Reference-Cited by-同舟云学术

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Paediatric Bone Age Assessment from Hand X-ray Using Deep Learning Approach

Published:2022 Issue: Volume: Page:373-383
ISSN:2367-3370
Container-title:Advances in Computing Systems and Applications
language:
Short-container-title:

Author:

Zerari Achouak,Djedidi Oussama^ORCID,Kahloul Laid^ORCID,Carlo Romeo^ORCID,Remadna Ikram

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-12097-8_32

Reference33 articles.

1. Albawi, S., Mohammed, T.A., Al-Zawi, S.: Understanding of a convolutional neural network. In: 2017 International Conference on Engineering and Technology (ICET), pp. 1–6. IEEE (2017)

2. Awad, M., Khanna, R.: Support vector regression. In: Efficient Learning Machines, pp. 67–80. Springer, Heidelberg (2015)

3. Chen, X., Zhang, C., Liu, Y.: Bone age assessment with x-ray images based on contourlet motivated deep convolutional networks. In: 2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP), pp. 1–6. IEEE (2018)

4. Ćwiklicki, M., Duplaga, M., Klich, J.: The Digital Transformation of Healthcare: Health 4.0. Routledge, Abingdon (2021)

5. Da Cunha, A.L., Zhou, J., Do, M.N.: The nonsubsampled contourlet transform: theory, design, and applications. IEEE Trans. Image Process. 15(10), 3089–3101 (2006)

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