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

Orhan, Kaan; Şevki Bayrakdar, İbrahim; Ezhov, Matvey; Kravtsov, Alexander; Özyürek, Taha

doi:10.1111/iej.13265

Public

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

Published in International Endodontic Journal • Jan 10, 2020

Authors:

Kaan Orhan

İbrahim Şevki Bayrakdar

Matvey Ezhov

Abstract

AIM: To verify the diagnostic performance of an artificial intelligence system based on the deep convolutional neural network method to detect periapical pathosis on cone-beam computed tomography (CBCT) images. METHODOLOGY: images of 153 periapical lesions obtained from 109 patients were included. T...

Subject

Cone beam computed tomography

Convolutional neural network

Segmentation

Finding related papers...

Discussions

(0)

No comments yet

Be the first to share your thoughts!