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RETINAL VASCULAR SYSTEM EDGE DETECTION BASED ON WAVELET IMAGE FUSION AND FIRST ORDER DERIVATIVE ALGORITHMS
Abstract
A vital role in detecting eye disorders is played by the analysis of the human retina using medical imaging methods. The main objective of this study is to improve the detection of retinal blood vessels by ameliorating the overall quality of non-uniform illumination conditions, removing image artifacts, connecting the broken vessels, and generating accurate segmented retinal vascular systems. A three-stage edge detection framework is proposed. First, image denoising, contrast enhancement, stretched decorrelation and image sharpening are performed. Then, edge detection operators to extract retinal vascular trees are adopted. Their output images are fused in pairs of two using a wavelet-based method with the objective to improve the accuracy of the extracted retinal vascular structure and connect discontinuous vessels. The performance of the fusion algorithm is assessed by comparing the blood vessel diameter values over the fused, first order derivative operators generated and ground truth images. The error rate and a structural similarity metric are calculated and are regarded as a performance analysis tool. The experimental results showed that the wavelet based fusion method was feasible and effective for an accurate edge detection process.
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Delibasis K.K., Kechriniotis A.I., Tsonos C., Assimakis N., Automatic model-based tracing algorithm for vessel segmentation and diameter estimation, Computer Methods and Programs in Biomedicine, vol. 100/issue 2, pp. 108 122, 2010.
Al-Diri B., Hunter A., Steel D., An active contour for segmenting and measuring retinal vessel, IEEE Trans. on Medical Imaging, vol. 28/ issue 9, pp. 1488 1497, 2010.
Gupta S., Mazumdar S.G., Sobel Edge Detection Algorithm, International Journal of Computer Science and Management Research, vol. 2/issue 2, pp. 1578-1583, 2013.
Bortolin Jr. S., Welfer D., Automatic detection of microaneurysms and haemorrhages in colour eye fundus images, International Journal of Computer Science & Information Technology, vol. 5/issue 5, pp. 21 37, 2013.
Moraru L., Obreja C.D., Retinal vessel enhancement based on Gaussian function, AIP Conference Proceedings, vol. 1796/issue 1, 040007-1, 2017. DOI: 10.1063/1.4972385
Dhanushkodi S.S.R., Manivannan V., Diagnosis system for diabetic retinopathy to prevent vision loss, Applied Medical Informatics, vol. 33/issue 3, pp. 1 11, 2013.
Adlakha D., Adlakha D., Tanwar R., Analytical Comparison between Sobel and Prewitt Edge Detection Techniques, International Journal of Scientific & Engineering Research, vol. 7/issue 1, pp. 1482-1485, 2016.
Moraru L., Obreja C.D., Dey N., Ashour A.S., Dempster-Shafer Fusion for Effective Retinal Vessels' Diameter Measurement, chapter in book: Soft Computing in Medical Image Analysis, Elsevier S&T Books, Eds. by Nilanjan Dey, Amira S. Ashour, Fuqian Shi, Valentina, E. Balas, pp. 149-160, 2018.
Martinez-Perez M.E., Hughes A.D., Thom S.A., Bharath A.A., Parker K.H., Segmentation of blood vessels from red-free and fluorescein retinal images, Medical Image Analysis, vol. 11/issue 4, pp. 47 61, 2007.
Acharjya P.P., Das R., Ghoshal D., Study and Comparison of Different Edge Detectors for Image Segmentation, Global Journal of Computer Science and Technology Graphics & Vision, vol. 12/issue 13, 2012.
DRIVE: Digital Retinal Images for Vessel Extraction (Image Sciences Institute, University Medical Center Utrecht), http://www.isi.uu.nl/Research/Databases/DRIVE/, 2004.
Staal J.J., Abramoff M.D., Niemeijer M., Viergever M.A., van Ginneken B., Ridge based vessel segmentation in color images of the retina, IEEE Transactions on Medical Imaging, vol. 23, pp. 501-509, 2004.
Maitra I.K., Nag S., Bandyopadhyay S.K., Technique for preprocessing of digital mammogram, Computer Methods and Programs In Biomedicine, vol. 107/issue 2, pp. 175 188 2012.
Nagendra G., Sridhar V., Prameelamma M., Zubair M., Fingerprint image enhancement using filtering techniques, International Journal of Computer Science Engineering, vol. 1/issue 1, pp.61-78, 2012.
Moraru L., Obreja C.D., Moldovanu S., Assessment of Vessel Diameters for MR Brain Angiography Processed Images, AIP Conference Proceedings, vol. 1694/issue 1, 040008, 2015. DOI: 10.1063/1.4937260
A. Sathesh, De-correlation stretch filtering approach for effective Poisson reduction in galaxy Images, International Journal of Computers & Technology, vol. 11/issue 9, pp. 2987-2993, 2013.
Archana J.N, Aishwarya P., A Review on the Image Sharpening Algorithms using Unsharp Masking, International Journal of Engineering Science and Computing, vol. 6/issue 7, pp. 8729-8733, 2016.
Panetta K., Zhou Y., Agaian S., Jia H., Nonlinear Unsharp Masking for Mammogram Enhancement, IEEE Transactions on Information Technology in Biomedicine, vol. 15/issue 6, pp. 918 928, 2011.
Patil S.M., Image Fusion using Wavelet Transform, International Journal of Engineering and Advanced Technology, vol. 5/issue 4, pp. 66-69, 2016.
Kalavathi P., Priya T., Segmentation of Brain Tissue in MR Brain Image using Wavelet Based Image Fusion with Clustering Technique, Computational Methods, Communication Techniques and Informatics, pp. 28-33, 2017.
Chen G.H., Yang C.L., Po L.M., Xie S.L., Edge-based structural similarity for image quality assessment, IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 2, pp. 933-936, 2006.
Betrabet S., Bhogayta C.K., Structural Similarity based Image Quality Assessment using full reference method, International Journal of Scientific Engineering and Technology, vol. 4/issue 4, pp. 252-255, 2015.
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