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Cha JW, Singh VR, Kim KH, Subramanian J, Peng Q, Yu H, Nedivi E, So PTC. Reassignment of scattered emission photons in multifocal multiphoton microscopy. Sci Rep 2014; 4:5153. [PMID: 24898470 PMCID: PMC4046171 DOI: 10.1038/srep05153] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2014] [Accepted: 05/14/2014] [Indexed: 01/02/2023] Open
Abstract
Multifocal multiphoton microscopy (MMM) achieves fast imaging by simultaneously scanning multiple foci across different regions of specimen. The use of imaging detectors in MMM, such as CCD or CMOS, results in degradation of image signal-to-noise-ratio (SNR) due to the scattering of emitted photons. SNR can be partly recovered using multianode photomultiplier tubes (MAPMT). In this design, however, emission photons scattered to neighbor anodes are encoded by the foci scan location resulting in ghost images. The crosstalk between different anodes is currently measured a priori, which is cumbersome as it depends specimen properties. Here, we present the photon reassignment method for MMM, established based on the maximum likelihood (ML) estimation, for quantification of crosstalk between the anodes of MAPMT without a priori measurement. The method provides the reassignment of the photons generated by the ghost images to the original spatial location thus increases the SNR of the final reconstructed image.
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Affiliation(s)
- Jae Won Cha
- 1] Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, MA 02139 [2]
| | - Vijay Raj Singh
- 1] Singapore-MIT Alliance for Research and Technology (SMART), BioSyM, Singapore 138602 [2]
| | - Ki Hean Kim
- Pohang University of Science and Technology, Department of Mechanical Engineering, Pohang 790-784, KOREA
| | - Jaichandar Subramanian
- Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, MA 02139
| | - Qiwen Peng
- 1] Institute of Bioengineering and Nanotechnology, A*Star, Singapore 138669 [2] Singapore-MIT Alliance, Computation and System Biology, Singapore 117576
| | - Hanry Yu
- 1] Singapore-MIT Alliance for Research and Technology (SMART), BioSyM, Singapore 138602 [2] Institute of Bioengineering and Nanotechnology, A*Star, Singapore 138669 [3] National University of Singapore, School of Medicine, Singapore 119077
| | - Elly Nedivi
- 1] Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, MA 02139 [2] Massachusetts Institute of Technology, Departments of Biology, and Brain and Cognitive Sciences, Cambridge, MA 02139
| | - Peter T C So
- 1] Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, MA 02139 [2] Singapore-MIT Alliance for Research and Technology (SMART), BioSyM, Singapore 138602 [3] Massachusetts Institute of Technology, Department of Biomedical Engineering, Cambridge, MA 02139
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Furia L, Pelicci PG, Faretta M. A computational platform for robotized fluorescence microscopy (I): high-content image-based cell-cycle analysis. Cytometry A 2013; 83:333-43. [PMID: 23463605 DOI: 10.1002/cyto.a.22266] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2012] [Revised: 01/11/2013] [Accepted: 01/23/2013] [Indexed: 12/28/2022]
Abstract
Hardware automation and software development have allowed a dramatic increase of throughput in both acquisition and analysis of images by associating an optimized statistical significance with fluorescence microscopy. Despite the numerous common points between fluorescence microscopy and flow cytometry (FCM), the enormous amount of applications developed for the latter have found relatively low space among the modern high-resolution imaging techniques. With the aim to fulfill this gap, we developed a novel computational platform named A.M.I.CO. (Automated Microscopy for Image-Cytometry) for the quantitative analysis of images from widefield and confocal robotized microscopes. Thanks to the setting up of both staining protocols and analysis procedures, we were able to recapitulate many FCM assays. In particular, we focused on the measurement of DNA content and the reconstruction of cell-cycle profiles with optimal parameters. Standard automated microscopes were employed at the highest optical resolution (200 nm), and white-light sources made it possible to perform an efficient multiparameter analysis. DNA- and protein-content measurements were complemented with image-derived information on their intracellular spatial distribution. Notably, the developed tools create a direct link between image-analysis and acquisition. It is therefore possible to isolate target populations according to a definite quantitative profile, and to relocate physically them for diffraction-limited data acquisition. Thanks to its flexibility and analysis-driven acquisition, A.M.I.CO. can integrate flow, image-stream and laser-scanning cytometry analysis, providing high-resolution intracellular analysis with a previously unreached statistical relevance.
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Affiliation(s)
- Laura Furia
- Department of Experimental Oncology, European Institute of Oncology, IFOM-IEO Campus for Oncogenomics, Milano 20139, Italy
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Rajwa B. Image cytometry goes multiphoton. Cytometry A 2007; 71:973-5. [PMID: 18023066 DOI: 10.1002/cyto.a.20479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Bartek Rajwa
- Purdue University Cytometry Laboratories, Bindley Bioscience Center, West Lafayette, Indiana 47907, USA.
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