Skip to main content
SpringerLink
Log in

Various Noises in Medical Images and De-noising Techniques

  • Conference paper
  • First Online:
Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 121))

  • 896 Accesses

Abstract

It has become a great topic to be researched for the better interpretation of the medical images. There are many de-noising techniques and filters available till now but still it is the topic of research. How, it is to get the fully de-noised image using any of the filtering techniques invented yet or using new idea of filtering. Wiener filtering is one of the most popular methods. Wavelets transform has become a very powerful tool for removing the noise from the images. Some of the noise cannot be ignored from the images while diagnosis. So, it is very important to remove the noise from such types of images. Numerous research papers have been published regarding this topic but still the research is going on to get fully de-noised medical images.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Hathaliya, J., Tanwar, S., Tyagi, S., Kumar, N.: Securing electronics healthcare records in healthcare 4.0: a biometric-based approach. Comput. Electr. Eng. 76, 398–410 (2019)

    Article  Google Scholar 

  2. Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12, 629–639 (1990)

    Article  Google Scholar 

  3. Kumar, N., Nachmani, M.: Noise removal and filtering techniques used in medical images. Orient. J. Comput. Sci. Technol. 10(1), 103–113 (2017)

    Google Scholar 

  4. Pizurica, A., Philips, W., Lemahieu, I., Acheroy, M.: A versatile wavelet domain noise filtration technique for medical imaging. IEEE Trans. 22, 323–331 (2003)

    Google Scholar 

  5. Tomasi, C., Manduchi, R.: Bilateral filter for gray and color images. In: IEEE Sixth International Conference on Computer Vision, Jan 1998, pp. 839–864

    Google Scholar 

  6. Kalra, M.K., Maher, M.M., D’Souza, R., Saini, S.: Multi detector computed tomography technology: current status and emerging developments. J. Comput. Assist. Tomogr. 28, S2–S6 (2004)

    Article  Google Scholar 

  7. Digenis, G.A., Sandefer, E.P., Page, R.C., Doll, W.J.: Gamma scintigraphy: an evolving technology in pharmaceutical formulation development-Part 1. Pharm. Sci. Technol. Today I, 100–108 (1998)

    Google Scholar 

  8. Amine, A., Rziza, M., Aboutajdine, D.: Noise reduction in medical images-comparison of noise removal algorithm, Oct 2012

    Google Scholar 

  9. Gupta, R., Tanwar, S., Tyagi, S., Kumar, N., Obaidat, M.S., Sadoun, B.: HaBiTs: blockchain based telesurgery framework for healthcare 4.0. In: International Conference on Computer, Information and Telecommunication Systems (IEEE CITS-2019), Beijing, China, 28–31 Aug 2019, pp. 6–10

    Google Scholar 

  10. Vora, J., Devmurari, P., Tanwar, S., Tyagi, S., Kumar, N., Obaidat, M.S.: Blind signatures based secured E-healthcare system. In: International Conference on Computer, Information and Telecommunication Systems (IEEE CITS-2018), Colmar, France, 11–13 July 2018, pp. 177–181

    Google Scholar 

  11. Pizurica, A., Wink, A.M., Vansteenkiste, E., Philips, W., Roedrdink, J.: A review of wavelet denoising in MRI and ultrasound brain imaging. Curr. Med. Imaging Rev., Bentham Sci. 2, 247–260 (2006)

    Google Scholar 

  12. Bao, P., Zhang, L.: Noise reduction for magnetic resonance images via adaptive multiscale products thresholding. IEEE Trans. Med. Imaging 22, 1089–1099 (2003). http://www.springer.com/lncs. Last accessed 2016/11/21

  13. Lee, J.S.: Digital image smoothing and the sigma filter. Comput. Vis., Graph. Image Process. 24, 255–269 (1983)

    Google Scholar 

  14. Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation noise removal algorithms. Phys. D: Nonlinear Phenom. 60, 259–268 (1992)

    Google Scholar 

  15. Kumari, A., Tanwar, S., Tyagi, S., Kumar, N.: Fog computing for healthcare 4.0 environment: opportunities and challenges. Comput. Electr. Eng. 72, 1–13 (2018)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Institute of Technology Uttarakhand, Srinagar, Pauri Garhwal, Uttarakhand, India

    Alamgeer Ali & Kamal Kumar

Authors
  1. Alamgeer Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kamal Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alamgeer Ali .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India

    Pradeep Kumar Singh

  2. Faculty of Mathematics, Physics, and Informatics, University of Gdańsk, Gdańsk, Poland

    Wiesław Pawłowski

  3. Department of Computer Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India

    Sudeep Tanwar

  4. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Neeraj Kumar

  5. The National Institute of Telecommunications (Inatel), Santa Rita do Sapucaí, Brazil

    Joel J. P. C. Rodrigues

  6. King Abdullah II School of Information Technology, University of Jordan, Amman, Jordan

    Mohammad Salameh Obaidat

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ali, A., Kumar, K. (2020). Various Noises in Medical Images and De-noising Techniques. In: Singh, P., Pawłowski, W., Tanwar, S., Kumar, N., Rodrigues, J., Obaidat, M. (eds) Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019). Lecture Notes in Networks and Systems, vol 121. Springer, Singapore. https://doi.org/10.1007/978-981-15-3369-3_23

Download citation

Publish with us

Policies and ethics

Search

Navigation