Multichannel Image Mosaicing of Stem Cells
Image mosaicing techniques are usually employed to offer researchers a wider field of view of microscopic image of biological samples. a mosaic is commonly achieved using automated microscopes and often with one “color" channel, whether it refers to natural or fluorescent analysis. In this work we present a method to achieve three subsequent mosaics of the same part of a stem cell culture analyzed in phase contrast and in fluorescence, with a common non-automated inverted microscope. The mosaics obtained are then merged together to mark, in the original contrast phase images, nuclei and cytoplasm of the cells referring to a mosaic of the culture, rather than to single images. The experiments carried out prove the effectiveness of our approach with cultures of cells stained with calcein (green/cytoplasm and nuclei) and hoechst (blue/nuclei) probes.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075673Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1113
 I. Tognarini, S. Sorace, R. Zonefrati, G. Galli, A. Gozzini, S. C. Sala, G. Thyrion, A. Carossino, A. Tanini, C. Mavilia, C. Azzari, F. Sbaiz, A. Facchini, R. Capanna, and M. Brandi, "In vitro differentiation of human mesenchymal stem cells on ti6al4v surfaces," Biomaterials, vol. 29, pp. 809-824, 2008.
 K. S. Fubito Toyama and J. Miyamichi, "Image mosaicing from a set of images without configuration information," in Proceedings of the 17th International Conference on Pattern Recognition (ICPR┼á04), Cambridge UK, August 23, vol. 2, 2004, pp. 899-902.
 K. Loewke, D. Camarillo, W. Piyawattanametha, D. Breeden, and K. Salisbury, "Real-time image mosaicing with a hand-held dual-axes confocal microscope," in Proceedings of the SPIE Conf. on Endoscopic Microscopy III, San Jose, CA, USA, January 20, vol. 6851, 2008, pp. 1-9.
 Y. Pang, A. A. Ucuzian, A. Matsumura, E. M. Brey, A. A. Gassman, V. A. Husak, and H. P. Greisler, "The temporal and spatial dynamics of microscale collagen scaffold remodeling by smooth muscle cells," Biomaterials, vol. 30, no. 11, pp. 2023-2031, Apr. 2009.
 H. S. Kim, J. P. Schulze, A. C. Cone, G. E. Sosinsky, and M. E. Martone, "Multi-channel transfer function with dimensionality reduction," in Conference on Visualization and Data Analysis, IS&T/SPIE┼ás International Symposium on Electronic Imaging, 2010, pp. 1-12.
 J. Y. Bouguet, "Pyramidal implementation of the Lukas Kanade feature tracker: Description of the algorithm," In Intel Research Laboratory, Technical Report, pp. 1-9, 1999.
 J. Shi and C. Tomasi, "Good features to track," in Proceedings of Computer Vision and Pattern Recognition, 1994, pp. 593-600.
 H. Foroosh, J. B. Zerubia, and M. Berthod, "Extension of phase correlation to subpixel registration," IEEE Transactions on Image Processing, vol. 14, no. 1, pp. 12-22, 2002.
 M. A. Fischler and R. C. Bolles, "Random sample and consensus: A paradigm for model fitting with application to image analysis and automated cartography," Comm. of the ACM, vol. 24, no. 6, pp. 381- 395, 1981.
 A. Bevilacqua, A. Gherardi, L. Carozza, and F. Piccinini, "Semiautomatic background detection in microscopic images," in International Conference on Biological Science and Engineering (ICBSE), Venice, Italy, November 24-26, 2010.
 P. Azzari and A. Bevilacqua, "Joint spatial and tonal mosaic alignment for motion detection with ptz camera," Lecture Notes in Computer Science, vol. 4142, pp. 764-775, 2006.
 E. Dougherty, An Introduction to Morphological Image Processing. SPIE-International Society for Optical Engine, Feb. 1992.