A content-based image retrieval system for echo images using SQL-based clustering approach

REFERENCES

• Nandagopalan S, Adiga BS, Deepak N. A universal model for content-based image retrieval. Int. J. Comput. Sci., 2009, 4, 242–245.
   Google Scholar
• Pitchaimalai SK, Ordonez C, Garcia-Alvarado C. Efficient distance computation using SQL queries and UDFs, Proc. 8th IEEE Int. Conf. on Data mining: ICDM 2008, Pisa, Italy,December 2008, IEEE Computer Society, pp. 533–542.
   Google Scholar
• Ordonez C. Integrating k-means clustering with a relational DBMS using SQL. IEEE Trans. Knowl. Data Eng., 2006, 18, 188–201.
   Web of Science ®Google Scholar
• Nandagopalan S, Adiga BS, Dhanalakshmi C, Deepak N. A fast k-means algorithm for the segmentation of echocardiographic images using DBMS-SQL, Proc. 2nd Int. Conf. on Computer and automation engineering: ICCAE 2010, Singapore,February 2010, ACSS, pp. 162–166.
   Google Scholar
• Feigenbaum H. Echocardiograohy, 5th editon, 1993 (Williams & Wilkins, Baltimore, MD).
   Google Scholar
• Nandagopalan S, Adiga BS, Dhanalakshmi C, Deepak N. Automatic segmentation and ventricular border detection of 2D echocardiographic images combining k-means clustering and active contour model, Proc. 2nd Int. Conf. on Computer and network technology: ICCNT 2010, Bangkok, Thailand,April 2010, IEEE Computer Society, pp. 447–451.
   Google Scholar
• Nandagopalan S, Adiga BS, Dhanalakshmi C, Deepak N. Color Doppler echocardiographic image analysis via shape and texture features, Proc. 2010 Int. Conf. on Bioinformatics and biomedical technology: ICBBT 2010, Chengdu, China,April 2010, IEEE Computer Society, pp. 139–143.
   Google Scholar
• Marsousi M, Eftekhari A, Kocharian A, Alirezaie J. Endocardial boundary extraction in left ventricular echocardiographic images using fast and adaptive B-spline snake algorithm. Int. J. Comput. Assist. Radiol. Surg., 2010, 5, 501–513.
   PubMed Web of Science ®Google Scholar
• Lang RM, Bierig M, Devereux RB, Flachskampf FA, Foster E, Pellikka PA, Picard MH, Roman MJ, Seward J, Shanewise JS, Solomon SD, Spencer KT, Sutton MS, Stewart WJ; Chamber Quantification Writing Group; American Society of Echocardiography’s Guidelines and Standards Committee; European Association of Echocardiography. Recommendations for chamber quantification: a report from the American Society of Echocardiography’s Guidelines and Standards Committee and the Chamber Quantification Writing Group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. J. Am. Soc. Echocardiogr., 2005, 18, 1440–1463.
   PubMed Web of Science ®Google Scholar
• Weber R, Mlivoncic M. Efficient region based image retrieval, Proc. 12th Int. Conf. on Information and knowledge management: CIKM’03, New Orleans, LA, USA,November 2003, ACM, Paper No. IMS 162.
   Google Scholar
• Lehmann TM, Güld MO, Deselaers T, Keysers D, Schubert H, Spitzer K, Ney H, Wein BB. Automatic categorization of medical images for content-based retrieval and data mining. Comput. Med. Imaging Graph., 2005, 29, 143–155.
   PubMed Web of Science ®Google Scholar
• Xue ZY, Antani S, Long LR, Jeronimo J, Thoma GR. Investigating CBIR techniques for cervicographic images. AMIA Annu Symp Proc., 2007, 2007, 826–830.
   Google Scholar
• Kak A, Pavlopoulou C. Content-based image retrieval from large medical databases, Proc. 1st Int. Symp. on 3D data processing visualization and transmission: 3DPVT’02, Padova, Italy,June 2002, IEEE Computer Society, pp. 138–147.
   Google Scholar
• Traina AJM, Castañón CAB, Traina C. MultiWaveMed: a system for medical image retrieval through wavelets transformations, Proc. 16th IEEE Symp. on Computer-based medical systems: CBMS’03, New York, USA,June 2003, IEEE Computer Society, pp. 150–155.
   Google Scholar
• Glatard T, Montagnat J, Magnin IE. Texture based medical image indexing and retrieval application to cardiac imaging, Proc. 6th ACM SIGMM Int. Workshop on Multimedia information retrieval: MIR ’04, New York, USA,October 2004, ACM Press, pp. 135–142.
   Google Scholar
• Caselles V. A geometric models for active contours in image processing. Numer. Math., 1993, 66, 1–31.
   Web of Science ®Google Scholar
• Arevalillo-Herráez M, Domingo J, Ferri FJ. Combining similarity measures in content-based image retrieval. Pattern Recogn. Lett., 2008, 29, 2174–2181.
   Web of Science ®Google Scholar
• Dirk Neumann, Karl R. Gegenfurtner “Image Retrieval and Perceptual Similarity”, ACM Transactions on Applied Perception, Vol. 3, No. 1, January 2006, pp. 31–47.
   Google Scholar
• DoM. N. Vetterli “Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance”, IEEE Trans. Image Process. 2002, 11 (2), 146–158.
   Google Scholar