Constructing the First Convolutional Neural Network for Determining Damaged Bones and Normal Bones in X-Ray Images

Authors

  • Mishra A Center for Artificial Intelligence and Friction Stir Welding, Stir Research Technologies, India
  • Datta P Department of Electronics and Telecommunication, KIIT University, Bhubaneswar, India

DOI:

https://doi.org/10.26438/ijcse/v7i11.5255

Keywords:

Convolutional Neural Network, X-Ray images, Broken bones, Intact bones

Abstract

Deep learning technology applied to medical imaging may become the most disruptive technology radiology has seen since the advent of digital imaging. Most researchers believe that within next 15 years, deep learning based applications will take over human and not only most of the diagnosis will be performed by intelligent machines but will also help to predict disease, prescribe medicine and guide in treatment. In this case study, Convolutional Neural Network (CNN) has been constructed to determine the nature of bones i.e. whether it is broken or intact. Python is used as a basic language for coding purpose. It can be seen that after 50 epochs the validation accuracy is 96.39 %, it shows the ability of the model to generalize to new data.

References

[1] Zhang, L., Yang, F., Zhang, Y.D. and Zhu, Y.J., 2016, September. Road crack detection using deep convolutional neural network. In 2016 IEEE international conference on image processing (ICIP) (pp. 3708-3712). IEEE.

[2] Sahiner, B., Chan, H.P., Petrick, N., Wei, D., Helvie, M.A., Adler, D.D. and Goodsitt, M.M., 1996. Classification of mass and normal breast tissue: a convolution neural network classifier with spatial domain and texture images. IEEE transactions on Medical Imaging, 15(5), pp.598-610.

[3] Lo, S.C., Lou, S.L., Lin, J.S., Freedman, M.T., Chien, M.V. and Mun, S.K., 1995. Artificial convolution neural network techniques and applications for lung nodule detection. IEEE Transactions on Medical Imaging, 14(4), pp.711-718.

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Published

2019-11-30
CITATION
DOI: 10.26438/ijcse/v7i11.5255
Published: 2019-11-30

How to Cite

[1]
A. Mishra and P. Datta, “Constructing the First Convolutional Neural Network for Determining Damaged Bones and Normal Bones in X-Ray Images”, Int. J. Comp. Sci. Eng., vol. 7, no. 11, pp. 52–55, Nov. 2019.

Issue

Vol. 7 No. 11 (2019): IJCSE November Edition

Section

Research Article

License

Creative Commons License

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