Image mosaicing is a technique that permits to enlarge the field of view of a camera. For instance, it is employed to achieve panoramas with common cameras or even in scientific applications, to achieve the image of a whole culture in microscopical imaging. Usually, a mosaic of cell cultures is achieved through using automated microscopes. However, this is often performed in batch, through CPU intensive minimization algorithms. In addition, live stem cells are studied in phase contrast, showing a low contrast that cannot be improved further. We present a method to study the flat field from live stem cells images even in case of 100% confluence, this permitting to build accurate mosaics on-line using high performance algorithms.
[1] Emilie Flaberg, Per Sabelstrnaöm, Christer Strandh, and LaszloSzekely,
"Extended field laser confocal microscopy (eflcm): Combining automated
gigapixel image capture with in silico virtual microscopy," BMC
Med Imaging, vol. 8, pp. 1-13, 2008.
[2] Richard L. Mort, Thaya Ramaesh1, Dirk A. Kleinjan, Steven D. Morle,
and John D. West, "Mosaic analysis of stem cell function and wound
healing in the mouse corneal epithelium," BMC Developmental Biology,
vol. 9, no. 4, pp. 1-14, 2009.
[3] Y. G. Patel, K. S. Nehal, I. Aranda, Y. Li, A. C. Halpern, and M. Rajadhyaksha,
"Confocal reflectance mosaicing of basal cell carcinomas
in mohs surgical skin excisions," Journal of Biomedical Optics, vol. 12,
no. 3, pp. 034027-1-034027-10, May/June 2007.
[4] F. Sadeghian, Z. Seman, A. R. Ramli, B. H. Abdul Kahar, and M. Saripan,
"A framework for white blood cell segmentation in microscopic
blood images using digital image processing," Biological Procedures
Online, vol. 11, pp. 196-206, December 2009.
[5] Kang Li and Takeo Kanade, "Nonnegative mixed-norm preconditioning
for microscopy image segmentation," Lecture Notes in Computer
Science, vol. 5636, pp. 362-373, 2009.
[6] E. D. Cheng, S. Challa, R. Chakravorty, and J. Markham, "Microscopic
cell segmentation by parallel detection and fusion algorithm," in
Proc. of the 10th IEEE International Workshop on Multimedia Signal
Processing, 2008, pp. 94-100.
[7] N. N. Kachouie and P. W. Fieguth, "Background estimation for
microscopic cellular images," in IEEE International Conference on
Image Processing, San Diego, CA, USA, October 12-15, 2008, pp. 3040-
3043.
[8] Alessandro Bevilacqua, Alessandro Gherardi, Ludovico Carozza, and
Filippo Piccinini, "Semi-automatic background detection in microscopic
images," in International Conference on Biological Science and Engineering
(ICBSE), Venice, Italy, November 24-26, 2010.
[9] Bruce D. Lucas and Takeo Kanade, "An iterative image registration
technique with an application to stereo vision," in International Joint
Conference on Artificial Intelligence, 1981, pp. 674-679.
[10] J. Y. Bouguet, "Pyramidal implementation of the Lukas Kanade feature
tracker: Description of the algorithm," In Intel Research Laboratory,
Technical Report, 1999.
[11] 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.
[12] 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.
[1] Emilie Flaberg, Per Sabelstrnaöm, Christer Strandh, and LaszloSzekely,
"Extended field laser confocal microscopy (eflcm): Combining automated
gigapixel image capture with in silico virtual microscopy," BMC
Med Imaging, vol. 8, pp. 1-13, 2008.
[2] Richard L. Mort, Thaya Ramaesh1, Dirk A. Kleinjan, Steven D. Morle,
and John D. West, "Mosaic analysis of stem cell function and wound
healing in the mouse corneal epithelium," BMC Developmental Biology,
vol. 9, no. 4, pp. 1-14, 2009.
[3] Y. G. Patel, K. S. Nehal, I. Aranda, Y. Li, A. C. Halpern, and M. Rajadhyaksha,
"Confocal reflectance mosaicing of basal cell carcinomas
in mohs surgical skin excisions," Journal of Biomedical Optics, vol. 12,
no. 3, pp. 034027-1-034027-10, May/June 2007.
[4] F. Sadeghian, Z. Seman, A. R. Ramli, B. H. Abdul Kahar, and M. Saripan,
"A framework for white blood cell segmentation in microscopic
blood images using digital image processing," Biological Procedures
Online, vol. 11, pp. 196-206, December 2009.
[5] Kang Li and Takeo Kanade, "Nonnegative mixed-norm preconditioning
for microscopy image segmentation," Lecture Notes in Computer
Science, vol. 5636, pp. 362-373, 2009.
[6] E. D. Cheng, S. Challa, R. Chakravorty, and J. Markham, "Microscopic
cell segmentation by parallel detection and fusion algorithm," in
Proc. of the 10th IEEE International Workshop on Multimedia Signal
Processing, 2008, pp. 94-100.
[7] N. N. Kachouie and P. W. Fieguth, "Background estimation for
microscopic cellular images," in IEEE International Conference on
Image Processing, San Diego, CA, USA, October 12-15, 2008, pp. 3040-
3043.
[8] Alessandro Bevilacqua, Alessandro Gherardi, Ludovico Carozza, and
Filippo Piccinini, "Semi-automatic background detection in microscopic
images," in International Conference on Biological Science and Engineering
(ICBSE), Venice, Italy, November 24-26, 2010.
[9] Bruce D. Lucas and Takeo Kanade, "An iterative image registration
technique with an application to stereo vision," in International Joint
Conference on Artificial Intelligence, 1981, pp. 674-679.
[10] J. Y. Bouguet, "Pyramidal implementation of the Lukas Kanade feature
tracker: Description of the algorithm," In Intel Research Laboratory,
Technical Report, 1999.
[11] 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.
[12] 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.
@article{"International Journal of Electrical, Electronic and Communication Sciences:55904", author = "Alessandro Bevilacqua and Alessandro Gherardi and Filippo Piccinini", title = "On-line Image Mosaicing of Live Stem Cells", abstract = "Image mosaicing is a technique that permits to enlarge the field of view of a camera. For instance, it is employed to achieve panoramas with common cameras or even in scientific applications, to achieve the image of a whole culture in microscopical imaging. Usually, a mosaic of cell cultures is achieved through using automated microscopes. However, this is often performed in batch, through CPU intensive minimization algorithms. In addition, live stem cells are studied in phase contrast, showing a low contrast that cannot be improved further. We present a method to study the flat field from live stem cells images even in case of 100% confluence, this permitting to build accurate mosaics on-line using high performance algorithms.
", keywords = "Microscopy, image mosaicing, stem cells.", volume = "4", number = "11", pages = "1630-4", }
