Artificial Intelligence (AI)-Based Systems for Automatic Skeletal Maturity Assessment through Bone and Teeth Analysis: A Revolution in the Radiological Workflow?
Articolo
Data di Pubblicazione:
2023
Citazione:
Artificial Intelligence (AI)-Based Systems for Automatic Skeletal Maturity Assessment through Bone and Teeth Analysis: A Revolution in the Radiological Workflow? / E. Caloro, M. Cè, D.M. Gibelli, A. Palamenghi, C. Martinenghi, G. Oliva, M. Cellina. - In: APPLIED SCIENCES. - ISSN 2076-3417. - 13:6(2023), pp. 3860.1-3860.10. [10.3390/app13063860]
Abstract:
Bone age is an indicator of bone maturity and is useful for the treatment of different pediatric conditions as well as for legal issues. Bone age can be assessed by the analysis of different skeletal segments and teeth and through several methods; however, traditional bone age assessment is a complicated and time-consuming process, prone to inter- and intra-observer variability. There is a high demand for fully automated systems, but creating an accurate and reliable solution has proven difficult. Deep learning technology, machine learning, and Convolutional Neural Networks-based systems, which are rapidly evolving, have shown promising results in automated bone age assessment. We provide the background of bone age estimation, its usefulness and traditional methods of assessment, and review the currently artificial-intelligence-based solutions for bone age assessment and the future perspectives of these applications.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
bone age assessment; artificial intelligence; machine learning; computer-aided detection; pediatric radiology
Elenco autori:
E. Caloro, M. Cè, D.M. Gibelli, A. Palamenghi, C. Martinenghi, G. Oliva, M. Cellina
Link alla scheda completa: