Prediction of chronic kidney disease stages by renal ultrasound imaging

References

• Arsanjani, R., X. Yuan, D. Dey, M. Fish, S. Dorbala, S. Hayes, D. Berman, G. Germano, and P. Slomka. 2013. “Improved Accuracy of Myocardial Perfusion SPECT for the Detection of Coronary Artery Disease Using a Support Vector Machine Algorithm.” Journal of Nuclear Medicine 54 (4): 549–555. doi:10.2967/jnumed.112.111542.
   PubMed Web of Science ®Google Scholar
• Bino, S. V., A. Unnikrishnan, and K. Balakrishnan. 2012. “Grey Level Co-Occurrence Matrices Generalisation and Some New Features.” International Journal of Computer Science, Engineering and Information Technology 2 (2): 151–157. doi:10.5121/ijcseit.2012.2213.
   Google Scholar
• Bradski, G. 2000. “The OpenCV library.” Dr. Dobb’s Journal of Software Tools, 25; 120-125.
   Google Scholar
• Chang, C.-C., and C.-J. Lin. 2011. “LIBSVM: A Library for Support Vector Machines.” ACM Transactions on Intelligent Systems and Technology (TIST) 2 (3): 27.
   Web of Science ®Google Scholar
• Chen, C.-J., T.-W. Pai, H. Fujita, C.-H. Lee, Y.-T. Chen, K.-S. Chen, and Y.-C. Chen. 2014. “Stage Diagnosis for Chronic Kidney Disease Based on Ultrasonography.” Proceedings of IEEE 2014 International Conference on Fuzzy Systems and Knowledge Discovery, 2014FSKD Proceeding, 534–539, Xiamen, China.
   Google Scholar
• Chronic Kidney Disease: National Clinical Guideline for Early Identification and Management in Adults in Primary and Secondary Care. National Collaborating Centre for Chronic Conditions (UK). London: Royal College of Physicians (UK), 2008. PMID:21413194.
   Google Scholar
• Corsonello, A., C. Pedone, F. Corica, C. Mussi, P. Carbonin, and R. A. Incalzi. 2005. “Concealed Renal Insufficiency and Adverse Drug Reactions in Elderly Hospitalized Patients.” Archives of Internal Medicine 165 (7): 790–795. doi:10.1001/archinte.165.7.790.
   PubMedGoogle Scholar
• Crowe, E., D. Halpin, and P. Stevens. 2008. “Guidelines: Early Identification and Management of Chronic Kidney Disease: Summary of NICE Guidance.” BMJ 337 (7673): 812–815. doi:10.1136/bmj.a1530.
   Google Scholar
• Eknoyan, G., and N. W. Levin. 2002. “K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification-Foreword.” American Journal of Kidney Diseases 39 (2): S14–S266.
   Web of Science ®Google Scholar
• Foley, R. N., P. S. Parfrey, and M. J. Sarnak. 1998. “Clinical Epidemiology of Cardiovascular Disease in Chronic Renal Disease.” American Journal of Kidney Diseases 32 (5): S112–S119.
   PubMed Web of Science ®Google Scholar
• Haralick, R. M., K. Shanmugam, and I. Dinstein. 1973. “Texture Features for Image Classification.” IEEE Transation on Systems, Man, and Cybernetics 3 (6): 610–621. doi:10.1109/TSMC.1973.4309314.
   Web of Science ®Google Scholar
• Jiang, H., R. Zheng, Y. Dehui, and D. Zhao. 2013. “A Novel Multiinstance Learning Approach for Liver Cancer Recognition on Abdominal CT Images Based on CPSO-SVM and IO.” Computational and Mathematical Methods in Medicine 2013: 1–10. doi:10.1155/2013/434969.
   Google Scholar
• Johnson, D. 2012. “Diagnosis, Classification and Staging of Chronic Kidney Disease.” Kidney Health Australia 2012, Retrieved from http://www.cari.org.au/CKD/CKD%20early/Diag_Classification_Staging_ECKD.pdf.
   Google Scholar
• Keith, D. S., G. A. Nichols, C. M. Gullion, J. B. Brown, and D. H. Smith. 2004. “Longitudinal Follow-Up and Outcomes among a Population with Chronic Kidney Disease in a Large Managed Care Organization.” Archives of Internal Medicine 164 (6): 659–663. doi:10.1001/archinte.164.6.659.
   PubMed Web of Science ®Google Scholar
• Kuo, B.-C., -H.-H. Ho, C.-H. Li, -C.-C. Hung, and J.-S. Taur. 2014. “A Kernel-Based Feature Selection Method for SVM with RBF Kernel for Hyperspectral Image Classification.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7 (1): 317–326. doi:10.1109/JSTARS.2013.2262926.
   Web of Science ®Google Scholar
• Kurella, M., G. M. Chertow, L. F. Fried, S. R. Cummings, T. Harris, E. Simonsick, S. Satterfield, H. Ayonayon, and K. Yaffe. 2005. “Chronic Kidney Disease and Cognitive Impairment in the Elderly: The Health, Aging, and Body Composition Study.” Journal of the American Society of Nephrology 16 (7): 2127–2133. doi:10.1681/ASN.2005010005.
   PubMed Web of Science ®Google Scholar
• Levey, A. S., and J. Coresh. 2012. “Chronic Kidney Disease.” The Lancet 379 (9811): 165–180. doi:10.1016/S0140-6736(11)60178-5.
   PubMed Web of Science ®Google Scholar
• Levey, A. S., J. Coresh, E. Balk, A. T. Kausz, A. Levin, M. W. Steffes, R. J. Hogg, R. D. Perrone, J. Lau, and G. Eknoyan. 2003. “National Kidney Foundation Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification.” Annals of Internal Medicine 139 (2): 137–147.
   PubMed Web of Science ®Google Scholar
• Levin, A., B. Hemmelgarn, B. Culleton, S. Tobe, P. McFarlane, M. Ruzicka, K. Burns, B. Manns, C. White, and F. Madore. 2008. “Guidelines for the Management of Chronic Kidney Disease.” Canadian Medical Association Journal 179 (11): 1154–1162. doi:10.1503/cmaj.080351.
   PubMed Web of Science ®Google Scholar
• Lorenzi, L., F. Melgani, and G. Mercier. 2013. “Missing-Area Reconstruction in Multispectral Images under a Compressive Sensing Perspective.” Geoscience and Remote Sensing, IEEE Transactions On 51 (7): 3998–4008. doi:10.1109/TGRS.2012.2227329.
   Web of Science ®Google Scholar
• Materka, A., and M. Strzelecki. 1998. “Texture Analysis Methods–A Review.” Technical university of lodz, institute of electronics, COST B11 report, Brussels:9–11.
   Google Scholar
• Phoon, R. K. 2012. “Chronic Kidney Disease in the Elderly - Assessment and Management.” Australian Family Physician 41 (12): 940–944.
   PubMedGoogle Scholar
• Pujari, R. M., and V. D. Hajare. 2014. “Analysis of Ultrasound Images for Identification of Chronic Kidney Disease Stages”.  International Conference on Networks & Soft Computing , 2014ICNSC Proceeding, 380-383, Guntur, India.
   Google Scholar
• Roderick, P. J., R. J. Atkins, L. Smeeth, D. M. Nitsch, R. B. Hubbard, A. E. Flectcher, and C. J. Bulpitt. 2008. “Detecting Chronic Kidney Disease in Older People; What are the Implications?” Age and Ageing 37 (2): 179–186. doi:10.1093/ageing/afm180.
   PubMed Web of Science ®Google Scholar
• Shlipak, M. G., C. Stehman-Breen, L. F. Fried, X. Song, D. Siscovick, L. P. Fried, B. M. Psaty, and A. B. Newman. 2004. “The Presence of Frailty in Elderly Persons with Chronic Renal Insufficiency.” American Journal of Kidney Diseases 43 (5): 861–867.
   PubMed Web of Science ®Google Scholar
• Wang, X.-Y., T. Wang, and B. Juan. 2011. “Color Image Segmentation Using Pixel Wise Support Vector Machine Classification.” Pattern Recognition 44 (4): 777–787. doi:10.1016/j.patcog.2010.08.008.
   Web of Science ®Google Scholar
• Wang, Z. 2014. “Support Vector Machine Learning-Based Cerebral Blood Flow Quantification for Arterial Spin Labeling MRI.” Human Brain Mapping 35 (7): 2869–2875. doi:10.1002/hbm.22445.
   PubMed Web of Science ®Google Scholar
• Weiner, D. E., H. Tighiouart, M. G. Amin, P. C. Stark, B. MacLeod, J. L. Griffith, D. N. Salem, A. S. Levey, and M. J. Sarnak. 2004. “Chronic Kidney Disease as a Risk Factor for Cardiovascular Disease and All-Cause Mortality: A Pooled Analysis of Community-Based Studies.” Journal of the American Society of Nephrology 15 (5): 1307–1315.
   PubMed Web of Science ®Google Scholar