A Novel Approach for Diagnosis of Glaucoma through Optic Nerve Head (ONH) Analysis using Fractal Dimension Technique
Автор: Dharmanna L, Chandrappa S, T. C. Manjunath, Pavithra G
Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs
Статья в выпуске: 1 vol.8, 2016 года.
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According to the survey of World Health Organization (WHO), the number of people getting affected by glaucoma eye disease in worldwide will be 79.11 million by the year 2020. Glaucoma is a dangerous eye disease, which can lead to permanent vision loss if not provided proper treatment at the right time. Currently ophthalmologists detect the glaucoma disease based on estimation of cup to disk ratio, but this method suffers from accurate segmentation of regions like optic disk and optic cup. However, this introduces errors in the diagnosis. Therefore in this paper, Hausdrop Fractal Dimension (HFD) technique is adopted for identification of the glaucoma eye disease. Here, Optic disk perimeter parameter is used in HFD technique for classification of healthy or glaucomatous retinas. Average fractal dimension is calculated for a set of healthy optic disks and the fractal dimension is found to be 0.998, whereas for glaucomatous optic disks obtained average fractal dimension value 1.342.
Glaucoma, Optic Cup, Optic Disk, Fractal Dimension, Optic Nerve Head, Cup to Disk Ratio, Hausdrop Fractal Dimension
Короткий адрес: https://sciup.org/15014832
IDR: 15014832
Список литературы A Novel Approach for Diagnosis of Glaucoma through Optic Nerve Head (ONH) Analysis using Fractal Dimension Technique
- Kolář, R., and P. Vacha. "Texture analysis of the retinal nerve fiber layer in fundus images via Markov random fields." World Congress on Medical Physics and Biomedical Engineering, September 7-12, 2009, Munich, Germany. Springer Berlin Heidelberg, 2009.
- Mishra, Madhusudan, Malaya Kumar Nath, and Samarendra Dandapat. "Glaucoma detection from color fundus images." International Journal of Computer & Communication Technology (IJCCT) 2.6 (2011): 7-10.
- Patton, Niall, et al. "Retinal image analysis: concepts, applications and potential." Progress in retinal and eye research 25.1 (2006): 99-127.
- Naz, Sobia, and Sheela N. Rao. "Glaucoma Detection in Color Fundus Images Using Cup to Disc Ratio." The International Journal of Engineering and Science (IJES) Vol 3: 51-58.
- Raj, Veena, and Vidya Devi. "Retinal Image Analysis Using Fovea Detection using Unsymmetrical Trimmed Median Filter (MDBUTMF)."
- Thorat, Sushma G. "Automated Glaucoma Screening using CDR from 2D Fundus Images." Editorial Committees.
- Ni, Soe Ni, PinaMarzilianol, and Hon-Tym Wong. "Angle closure glaucoma detection using fractal dimension index on SS-OCT images." Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE. IEEE, 2014.
- Zhang, Xusheng, et al. "Automated segmentation of intramacular layers in Fourier domain optical coherence tomography structural images from normal subjects." Journal of biomedical optics 17.4 (2012): 0460111-0460117.
- Bock, Rüdiger, et al. "Glaucoma risk index: automated glaucoma detection from color fundus images." Medical image analysis 14.3 (2010): 471-481.
- Burana-Anusorn, Chalinee, et al. "Image Processing Techniques for Glaucoma Detection Using the Cup-to-Disc Ratio." Thammasat International Journal of Science and Technology 18.1 (2013): 22.
- Meier, Jörg, et al. "Effects of preprocessing eye fundus images on appearance based glaucoma classification." Computer Analysis of Images and Patterns. Springer Berlin Heidelberg, 2007.
- Byahatti, Archana Nandibewoor SB Kulkarni Sridevi, and Ravindra Hegadi. "Computer Based Diagnosis of Glaucoma using Digital Fundus Images."Proceedings of the World Congress on Engineering. Vol. 3.2013.
- Patil, Dnyaneshwari D., Ramesh Manza, and Gangadevi C. Bedke. "Diagnose Glaucoma by proposed Image processing Methods." International Journal of Computer Applications 106.8 (2014).
- Malay Kishore Dutta, Amit Kumar Mourya, Anushikha Singh, M.Parthasarathi, "Glaucoma Detection by Segmenting the Super Pixels from Fundus Colour Retinal Images", IEEE, International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), 2014.
- Hafsah Ahmad, Abubakar Yamin, Aqsa Shakeel, "Detection of Glaucoma Using Retinal Fundus Images", IEEE, the 2013 Biomedical Engineering International Conference (BMEiCON-2013).
- Hafsah Ahmad, Abubakar Yamin, Aqsa Shakeel, "Detection of Glaucoma Using Retinal Fundus Images", IEEE, the 2013 Biomedical Engineering International Conference (BMEiCON-2013).
- S.Kavitha, S.Karthikeyan, Dr.K.Duraiswamy, "Neuroretinal rim Quantification in Fundus Images to Detect Glaucoma", IJCSNS International Journal of Computer Science and Network Security, VOL.10 No.6, June 2010.
