Acta Scientific Computer Sciences

Research Article Volume 4 Issue 6

Efficient Super-resolution For Chest X-rays

Karthik Sivarama Krishnan* and Koushik Sivarama Krishnan

Gen Nine Inc, United States

*Corresponding Author: Karthik Sivarama Krishnan, Gen Nine Inc, United States.

Received: April 30, 2022; Published: May 18, 2022

Abstract

High-resolution images are really helpful in various applications like medical diagnosis and hence the need for super-resolution has also increased significantly. Increasing the image resolution on various medical images like a chest X-ray or cell images can improve the accuracy of diagnosis by revealing previously unseen details. Using Image super-resolution also reduces the number of X-ray radiations required to render ultra high-quality imaging. Hence we applied super-resolution on X-rays using fine-tuned Swift-SRGAN architecture, which significantly improved the details on the chest X-rays. This helps in rendering super-resolution images from low-resolution images with less computational requirements. The proposed approach achieves a Structural Similarity Index Measure(SSIM) of 0.893 and a Peak Signal-to-Noise Ratio (PSNR) of 32.10.


Keywords: X-rays; Super-resolution; Swift-SRGAN; Generative Adversarial Network (GAN); Chest X-ray; Medical Imaging; Mobile Computing; Peak Signal-to-Noise Ratio (PSNR); Structural Similarity Index Measure (SSIM)

References

  1. Haque Md Inzamam Ul., et al. "The effect of image resolution on automated classification of chest x-rays”. medRxiv (2021).
  2. Zamzmi Ghada., et al. "Accelerating super-resolution and visual task analysis in medical images”. Applied Sciences12 (2020): 4282.
  3. Zhao Chao-Yue., et al. "Chest X-ray images super-resolution reconstruction via recursive neural network”. Multimedia Tools and Applications1 (2021): 263-277.
  4. Krishnan Koushik Sivarama and Karthik Sivarama Krishnan. "Vision Transformer based COVID-19 Detection using Chest X-rays”. 2021 6th International Conference on Signal Processing, Computing and Control (ISPCC). IEEE, (2021).
  5. K S Krishnan and K S Krishnan. "SwiftSRGAN - Rethinking Super-Resolution for Efficient and Real-time Inference". 2021 International Conference on Intelligent Cybernetics Technology and Applications (ICICyTA) (2021): 46-51.
  6. Krishnan Karthik Sivarama and Ferat Sahin. "ORBDeepOdometry-A feature-based deep learning approach to monocular visual odometry”. 2019 14th Annual Conference System of Systems Engineering (SoSE). IEEE (2019).
  7. Buslaev Alexander., et al. "Albumentations: fast and flexible image augmentations”. Information2 (2020): 125.
  8. Reza Ali M. "Realization of the contrast limited adaptive histogram equalization (CLAHE) for real-time image enhancement”. Journal of VLSI Signal Processing Systems for Signal, Image and Video Technology1 (2004): 35-44.
  9. Krishnan Karthik Sivarama and Koushik Sivarama Krishnan. "Benchmarking Conventional Vision Models on Neuromorphic Fall Detection and Action Recognition Dataset”. 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC). IEEE (2022).
  10. MEH Chowdhury., et al. "Can AI help in screening Viral and COVID-19 pneumonia?” IEEE Access 8 (2020): 132665-132676.
  11. Rahman T., et al. "Exploring the Effect of Image Enhancement Techniques on COVID-19 Detection using Chest X-ray Images” (2021).
  12. Bee Lim., et al. "Enhanced deep residual networks for single image super-resolution”. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops (2017): 136-144.
  13. Eirikur Agustsson and Radu Timofte. “Ntire 2017 challenge on single image super-resolution: Dataset and study”. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops (2017): 126-135.
  14. Radu Timofte., et al. "Ntire 2017 challenge on single image super-resolution: Methods and results”. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops (2017): 114-125.
  15. Ilya Loshchilov and Frank Hutter. “Fixing Weight Decay Regularization in Adam”. In: CoRR abs/1711.05101 (2017). arXiv: 1711.05101.
  16. Karthik Sivarama Krishnan., et al. "Recognition of human arm gestures using Myo armband for the game of hand cricket”. In: 2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS) (2017): 389-394.
  17. Van Ouwerkerk JD. "Image super-resolution survey”. Image and vision Computing10 (2006): 1039-1052.

Citation

Citation: Karthik Sivarama Krishnan and Koushik Sivarama Krishnan. “Efficient Super-resolution For Chest X-rays". Acta Scientific Computer Sciences 4.6 (2022): 46-50 .

Copyright

Copyright: © 2022 Karthik Sivarama Krishnan and Koushik Sivarama Krishnan. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




Metrics

Acceptance rate35%
Acceptance to publication20-30 days

Indexed In




News and Events


  • Certification for Review
    Acta Scientific certifies the Editors/reviewers for their review done towards the assigned articles of the respective journals.
  • Submission Timeline for Upcoming Issue
    The last date for submission of articles for regular Issues is December 25, 2024.
  • Publication Certificate
    Authors will be issued a "Publication Certificate" as a mark of appreciation for publishing their work.
  • Best Article of the Issue
    The Editors will elect one Best Article after each issue release. The authors of this article will be provided with a certificate of "Best Article of the Issue"

Contact US