Abstract
X-ray Mammography has been a common technique of breast cancer identification. A single X-ray mammogram will not be able to convey full information about cancer to the radiologist. In this, an image fusion using Weighted Average SWT is proposed and histogram equalization is performed to enhance the quality of the fused X-ray mammogram. The resultant X-ray mammogram is same as conventional X-ray mammogram but with appreciably superior detail and is then reconstructed by using its inverse transform. This fused X-ray mammogram is well-suited for clinical settings and equips the radiologist to use lifetime diagnosis experience in X-ray mammography.
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References
V.P.S. Naidu and J.R. Rao, “Pixel-level Image Fusion using Wavelets and Principal Component Analysis”, Defence Science Journal, Vol. 58, No. 3, May 2008, pp. 338–352.
A. P. James, B. V. Dasarathy, “Medical Image Fusion: A survey of the state of the art”, Information Fusion, 2014.
Jagalingam P., ArkalVittalHegde, “Pixel Level Image Fusion–A Review on Various Techniques”, 3rd World Conference on Applied Sciences, Engineering & Technology 27–29 September 2014, Kathmandu, Nepal.
Z. Wang, C.A. Clavijo, E. Roessl, U. van Stevendaal, T. Koehler, N. Hausergy and M. Stampanoni, “Image fusion scheme for differential phase contrast mammography”, 7th Medical Applications Of Synchrotron Radiation Workshop (MASR 2012) Shanghai Synchrotron Radiation Facility (SSRF), 17–20 October, 2012, Published By IOP Publishing For Sissa Media lab.
Tania Stathaki, 2008. “Image Fusion Algorithms and Applications”, Elsevier.
V. Jyothi, B. Rajesh Kumar, P.K. Rao, D.V.R.K. Reddy, “Image Fusion using Evolutionary Algorithms (GA)”, International Journal of Computer Technologies and Applications, 2(2), 2012.
M Prema Kumar and P Rajesh Kumar, “Image Fusion of Mammography Images using Genetic Algorithm (GA)”, Australian Journal of Basic and Applied Sciences, 9(33) October 2015, Pages: 45–50.
Luqman Maraaba, Zakariya Al-Hamouz, Hussain Al-Duwaish: Prediction of the Levels of Contamination of HV Insulators Using Image Linear Algebraic Features and Neural Networks, Arab J Sci Eng, 40 (9) 2609–2617 (2015).
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Kumar, M.P., Sowjanya, N., Kumar, P.R. (2018). Weighted Averaging SWT Technique for Enhanced Image Fusion in X-ray Mammography. In: Anguera, J., Satapathy, S., Bhateja, V., Sunitha, K. (eds) Microelectronics, Electromagnetics and Telecommunications. Lecture Notes in Electrical Engineering, vol 471. Springer, Singapore. https://doi.org/10.1007/978-981-10-7329-8_76
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DOI: https://doi.org/10.1007/978-981-10-7329-8_76
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