Abstract
Medical imaging modalities play a crucial part in the process of medical diagnosis. The medical images such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI) need to undergo the enhancement process which aids the medical specialists for the precise identification of illness in the patients. The enhancement techniques are worked on these medical images to improve the visual display for clear medical examining. Cardiac disease is one of the major health problems affecting the people globally. Cardiac magnetic resonance (CMR) imaging modality led to early detection of the cardiac-related ailments in the patients. Hence, it is needed to enhance these CMR images for the precise diagnosis by the medical experts. This paper explores the variety of enhancement methods to betterment the contrast, suppress the noise, enhance the edges, and to retain the naturalness of the medical images. The paper also reviews the enhancement techniques implemented in both spatial domain and frequency domain. Review and analysis of these techniques pave way for making decision to find the optimal algorithm suitable for enhancing the medical images.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
https://healthfully.com/12372451/advantages-disadvantages-of-x-rays [Accessed on 24.05.20]
https://www.diffen.com/difference/CT_Scan_vs_MRI [Accessed on 25.05.20]
M. Zibaei, Helminth infections and cardiovascular diseases. Current Cardiol. Rev. 13, 56–62 (2017). https://doi.org/10.2174/1573403X12666160803
J.C. Brenes, A. Doltra, S. Prat, Cardiac magnetic resonance imaging in the evaluation of patients with hypertrophic cardiomyopathy. Global Cardiol. Sci. Practice 2018(3) (2018). https://doi.org/10.21542/gcsp.2018.22
http://www.cardiacatlas.org [Accessed on 29.06.20]
R. C. Gonzalez, R.E. Woods, Digital Image Processing, 3rd edn. (Prentice-Hall, Inc. Upper Saddle River, J, USA ©2006, 2007)
B. Shashi, S. Rana, A review of medical image enhancement techniques for image processing. Int. J. Current Eng. Technol. 5(2), 1282–1286 (2011). https://doi.org/10.14741/ijcet/22774106/5.2.2015.121
V. Magudeeswaran, C.G. Ravichandran, P. Thirumurugan, Brightness preserving bi-level fuzzy histogram equalization for MRI brain image contrast enhancement. Int. J. Imaging Syst. Technol. 27(2), 153–161 (2017). https://doi.org/10.1002/ima.22219
S.S. Bhairannawar, Efficient Medical Image Enhancement Technique Using Transform HSV Space and Adaptive Histogram Equalization (Elsevier Inc., Soft Computing Based Medical Image Analysis, 2018). https://doi.org/10.1016/B978-0-12-813087-2.00003-8
J. Joseph et al., An objective method to identify optimum clip-limit and histogram specification of contrast limited adaptive histogram equalization for MR images. Biocybernet. Biomed. Eng. Nałęcz Institute Biocybernetics Biomed. Eng. Polish Acad. Sci. 37(3), 489–497 (2017). https://doi.org/10.1016/j.bbe.2016.11.006
Y. Chang et al., Automatic contrast-limited adaptive histogram equalization with dual gamma correction. IEEE Access 6, 11782–11792 (2018). https://doi.org/10.1109/ACCESS.2018.2797872
S. Patel et al., Comparative study on histogram equalization techniques for medical image enhancement. Adv. Intell. Syst. Comput. 1048, 657–669 (2020). https://doi.org/10.1007/978-981-15-0035-0_54
M. Zohaib et al., Image enhancement by using histogram equalization technique in Matlab. 7(2), 150–154 (2018)
C.F.J. Kuo, H.C. Wu, Gaussian probability bi-histogram equalization for enhancement of the pathological features in medical images. Int. J. Imaging Syst. Technol. 29(2), 132–145 (2019). https://doi.org/10.1002/ima.22307
M.M. Pawar, S.N. Talbar, Local entropy maximization based image fusion for contrast enhancement of mammogram. J. King Saud Univ.—Comput. Inf. Sci. https://doi.org/10.1016/j.jksuci.2018.02.008
Z. Li et al., An efficient and high quality medical CT image enhancement algorithm. Int. J. Imaging Syst. Technol. (June 2019), 1–11 (2020). https://doi.org/10.1002/ima.22417
R.M. Ghadban, Journal of AL-Qadisiyah for computer science and mathematics medical image enhancement based on adaptive histogram equalization and contrast stretching department of computer science. College Sci. Univ. Basrah, J. AL-Qadisiyah 6(1), 28–37 (2014)
S.C. Huang, F.C. Cheng, Y.S. Chiu, Efficient contrast enhancement using adaptive gamma correction with weighting distribution. IEEE Trans. Image Process. 22(3), 1032–1041 (2013). https://doi.org/10.1109/TIP.2012.2226047
L. Yao, S. Muhammad, A novel technique for analysing histogram equalized medical images using superpixels. Comput. Assisted Surgery Taylor Francis 24(1), 53–61 (2019). https://doi.org/10.1080/24699322.2018.1560100
G. Cao et al., Fast contrast enhancement by adaptive pixel value stretching. Int. J. Distrib. Sensor Networks 14(8) (2018). https://doi.org/10.1177/1550147718793803
M.S. Maheshan, B.S. Harish, N. Nagadarshan N, On the use of image enhancement technique towards robust sclera segmentation. Proc. Comput. Sci. 143, 466–473 (2018). https://doi.org/10.1016/j.procs.2018.10.419
S. Agrawal et al., A novel joint histogram equalization based image contrast enhancement. J. King Saud Univ.—Comput. Inf. Sci. King Saud Univ. (2019). https://doi.org/10.1016/j.jksuci.2019.05.010
M. Agarwal, R. Mahajan, Medical image contrast enhancement using range limited weighted histogram equalization. Proc. Comput. Sci. 125(2017), 149–156 (2018). https://doi.org/10.1016/j.procs.2017.12.021
S. Singh, R.K. Bansal, S. Bansal, Medical image enhancement using histogram processing techniques followed by median filter. Ijipa 3(1), 1–9 (2012)
M. Sahnoun et al., Spinal cord MRI contrast enhancement using adaptive gamma correction for patient with multiple sclerosis. Signal Image Video Process. 14(2), 377–385 (2020). https://doi.org/10.1007/s11760-019-01561-x
P. Yugander et al., MR image enhancement using adaptive weighted mean filtering and homomorphic filtering. Proc. Comput. Sci. 167(2019), 677–685 (2020). https://doi.org/10.1016/j.procs.2020.03.334
B. Subramani, M. Veluchamy, Quadrant dynamic clipped histogram equalization with gamma correction for color image enhancement. Color Res. Appl. 45(4), 644–655 (2020). https://doi.org/10.1002/col.22502
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Radhika, R., Mahajan, R. (2022). Medical Image Enhancement: A Review. In: Saraswat, M., Roy, S., Chowdhury, C., Gandomi, A.H. (eds) Proceedings of International Conference on Data Science and Applications . Lecture Notes in Networks and Systems, vol 288. Springer, Singapore. https://doi.org/10.1007/978-981-16-5120-5_9
Download citation
DOI: https://doi.org/10.1007/978-981-16-5120-5_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-5119-9
Online ISBN: 978-981-16-5120-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)