Visualization, Image Processing and Computation in Biomedicine
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Visualization, Image Processing and Computation in Biomedicine
Home > Journals > Visualization, Image Processing and Computation in Biomedicine > Volume 2, 2013 > Elementary Morphometric Labs-on-a-Chip Based on ...
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Home > Journals > Visualization, Image Processing and Computation in Biomedicine > Volume 2, 2013 > Elem entary Morphom etric Labs-on-a-Chip Based on Hem ocytom etric Cham bers w ith Radiofrequency Culture Identification and Relay of Spectrozonal Histochem ical Monitoring
Visualization, Image Processing and Computation in Biomedicine DOI: 10.1615/VisualizImageProcComputatBiomed.2013005968
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Elementary Morphometric Labs-on-a-Chip Based on Hemocytometric Chambers with Radiofrequency Culture Identification and Relay of Spectrozonal Histochemical Monitoring Alexander V. Notchenko Neuronal Brain Structure Lab oratory, Scientific Neurology Center, Russian Academy of Medical Sciences; Bauman Moscow State Technical University ISSN Online: 2162-3511
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You have access to: Volume 2, 2013 Volume 1, 2012
O. V. Gradov Neuronal Brain Structure Lab oratory, Scientific Neurology Center, Russian Academy of Medical Sciences; Institute of Chemical Physics, Russian Academy of Sciences
ABSTRACT An accessible design of autonomous labs-on-the-chip, which do not require a special reader but use grid hemocytometric counting chambers for sectioning the detected cells, isolated by a special device for cell sedimentation, is proposed. A system for automated radiofrequency (RF) identification of chambers in long-term storage conditions, which provides new morphometric data at various stages of cultivation or biomonitoring, is proposed. A new diffraction method for calculating and fingerprinting cellular structures in varying environmental conditions is described. Experimental data on the pilot testing of Fuchs-Rosenthal, Buerker, Neubauer, Makler, and Thoma chambers for the described technique are presented. The applicability of these devices for coherent-densitometric indication either of concentration dynamics in cell culture or of suspension and morphogenetic processes in them for laminar conditions is shown. A self-learning program for cellular pattern recognition and precision cytophotometry based on a lab-on-a-chip with micrometric object calibration relative to the counting net is demonstrated. A hybrid in vitro/in silico method of morphogenesis monitoring in cell cultures is introduced.
