Machine learning for image analysis in the cervical spine: Systematic review of the available models and methods

Author:

Goedmakers C.M.W.ORCID,Pereboom L.M.,Schoones J.W.ORCID,de Leeuw den Bouter M.L.ORCID,Remis R.F.,Staring M.ORCID,Vleggeert-Lankamp C.L.A.

Publisher

Elsevier BV

Reference67 articles.

1. Fully automatic cervical vertebrae segmentation framework for X-ray images;Al Arif;Comput. Methods Progr. Biomed.,2018

2. Improving an Active Shape Model with Random Classification Forest for Segmentation of Cervical Vertebrae;Al Arif,2016

3. Evaluation of a new approach to compute intervertebral disc height measurements from lateral radiographic views of the spine;Allaire;Eur. Spine J.,2017

4. Validation of cervical vertebral maturation stages: artificial intelligence vs human observer visual analysis;Amasya;Am. J. Orthod. Dentofacial Orthop.,2020

5. BACH: Grand challenge on breast cancer histology images;Aresta;Med. Image Anal.,2019

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