Evaluation of artificial intelligence for detecting periapical pathosis on cone‐beam computed tomography scans-Reference-Cited by-同舟云学术

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Evaluation of artificial intelligence for detecting periapical pathosis on cone‐beam computed tomography scans

Published:2020-05 Issue:5 Volume:53 Page:680-689
ISSN:0143-2885
Container-title:International Endodontic Journal
language:en
Short-container-title:Int Endod J

Author:

Orhan K.¹^ORCID,Bayrakdar I. S.²^ORCID,Ezhov M.³^ORCID,Kravtsov A.³^ORCID,Özyürek T.⁴^ORCID

Affiliation:

1. Department of Oral and Maxillofacial Radiology Faculty of Dentistry Ankara University AnkaraTurkey

2. Department of Oral and Maxillofacial Radiology Faculty of Dentistry Eskisehir Osmangazi University Eskişehir Turkey

3. Diagnocat Inc San Francisco CA USA

4. Department of Endodontics Faculty of Dentistry Istanbul Medeniyet University Istanbul Turkey

Publisher

Wiley

Subject

General Dentistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/iej.13265

Reference55 articles.

1. Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions

2. Use of cone-beam computed tomography in endodontics Joint Position Statement of the American Association of Endodontists and the American Academy of Oral and Maxillofacial Radiology

3. Contrast-enhanced computed tomography image assessment of cervical lymph node metastasis in patients with oral cancer by using a deep learning system of artificial intelligence

4. Deep Learning in Mammography

5. Automatic lesion detection and segmentation of 18F-FET PET in gliomas: A full 3D U-Net convolutional neural network study

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