Image processing and computer modelling are important tools in most medical imaging domains, and have also drawn the attention of the biological community to biological imaging applications. To date, many of biological data analysis necessitate a considerable degree of human intervention. Manual procedures are based on subjective human interpretation, are prone to large variability between the human experts, are time consuming and are of high cost. Automated tools are, thus, important in achieving objective and repetitive analysis, accurate quantitative measurements and the analysis of increasing data volumes. The objective of the present study is to develop an automatic tool to identify and classify the Rotavirus-A particles in digital microscopic images. Geometric features are used to identify and classify the Rotavirus-A particle. The proposed method yields 98% classification rate using 3 classifier.

1. Rafel C. Gonzalez and Richard E. Woods, “Digital Image Processing”, Pearson Education Asia (2002)
2. M. A. Hayat (2000). Principles and techniques of electron microscopy: biological applications. Cambridge University Press. pp. 45-61. ISBN 0521632870.
3. Bozzola, John J.; Russell, Lonnie D. (1999). "Specimen Preparation for Transmission Electron Microscopy". Electron microscopy : principles and techniques for biologists. Sudbury, Mass.: Jones and Bartlett. pp. 21–31. ISBN 9780763701925.
4. Velázquez FR, Matson DO, Calva JJ, Guerrero L, Morrow AL, Carter-Campbell S, Glass RI, Estes MK, Pickering LK, Ruiz-Palacios GM (1996). "Rotavirus infections in infants as protection against subsequent infections". N. Engl. J. Med. 335 (14): 1022–8. doi:10.1056/NEJM199610033351404. PMID 8793926.
5. Arnoldi F, Campagna M, Eichwald C, Desselberger U, Burrone OR (2007). "Interaction of rotavirus polymerase VP1 with nonstructural protein NSP5 is stronger than that with NSP2". J. Virol. 81 (5): 2128–37. doi:10.1128/JVI.01494-06. PMID 17182692. http://jvi.asm.org/ cgi/content/full/81/5/2128.
6. S. Venkataraman, D.P. Allison, H. Qi, J.L. Morrell-Falvey, N.L. Kallewaard, J.E. Crowe Jr. and M.J. Doktycz. “Automated image analysis of atomic force microscopy images of rotavirus particles.” Ultramicroscopy, Volume 106, Issues 8-9, June-July 2006, Pages 829-837.
7. Gerald J.F. Banon, Junior Barrera, Ulisses M. Braga-Neto (Eds.) “Mathematical Morphology and its Applications to Signal and Image Processing”, proceedings of the 8th international symposium on mathematical morphology (ISMM'07), ISBN 978-85-17-00032-4 (2007)
8. K. Parvati,1 B. S. Prakasa Rao,2 and M. Mariya Das3, “Image Segmentation Using Gray-Scale Morphology and Marker-Controlled Watershed Transformation”, Hindawi Publishing Corporation. Volume 2008 (2008), Article ID 384346, 8 pages
9. P.S. Hiremath and Parashuram Bannigidad , Automatic Classification of Bacterial Cells in Digital Microscopic Images, ICDIP 2010, February 26-28, 2010, Singapore.
10. Dennis Kunkel Microscopy, Inc, Science Stock Photography, [http://www.denniskunkel.com].
11. Qiang Wu, Fatima Merchant, Kenneth R. Castlem, “Microscope Image Processing”, Elsevier,2008.
12. Al Bovik, “Essential guide to Image processing”, Elsevier, ISBN: 978-0-12-374457-9 (2009).

Rotavirus-A image segmentation classification image analysis watershed segmentation 3σ classifier