8000 GitHub - gaanto/neural-orthodontic-cephalometry: Convolutional networks detection in cephalometry based on TensorFlow
[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to content

gaanto/neural-orthodontic-cephalometry

 
 

Repository files navigation

Neural Orthodontic Cephalometry

Source code for article "The efficiency of deep learning algorithms for detecting anatomical reference points on radiological images of the head profile".


made-with-python made-with-tensorflow made-with-numpy made-with-pandas made-with-scikit-learn


arXiv Code style: black


This repository describes the solution to the problem of detecting anatomical reference points on radiological images of the head profile for orthodontic analysis based on convolution neural networks. In this study, the definition of reference points on the radiological for cephalometry problems used.

The anatomical reference point detection process is defined as the task of localizing position in a reference point area with normal distribution. The maximum value of normal distribution is a desired anatomical reference point.

Training process animation

As the considered networks were selected convolutional networks of the sequential convolutional layers and U-Net architecture.

See more at:

License

License: MIT

This project is licensed under the terms of the MIT license (see LICENSE file).

About

Convolutional networks detection in cephalometry based on TensorFlow

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%
0