Literature DB >> 25309099

Quantitative Phase Microscopy: how to make phase data meaningful.

Goldie Goldstein1, Katherine Creath2.   

Abstract

The continued development of hardware and associated image processing techniques for quantitative phase microscopy has allowed superior phase data to be acquired that readily shows dynamic optical volume changes and enables particle tracking. Recent efforts have focused on tying phase data and associated metrics to cell morphology. One challenge in measuring biological objects using interferometrically obtained phase information is achieving consistent phase unwrapping and -dimensions and correct for temporal discrepanices using a temporal unwrapping procedure. The residual background shape due to mean value fluctuations and residual tilts can be removed automatically using a simple object characterization algorithm. Once the phase data are processed consistently, it is then possible to characterize biological samples such as myocytes and myoblasts in terms of their size, texture and optical volume and track those features dynamically. By observing optical volume dynamically it is possible to determine the presence of objects such as vesicles within myoblasts even when they are co-located with other objects. Quantitative phase microscopy provides a label-free mechanism to characterize living cells and their morphology in dynamic environments, however it is critical to connect the measured phase to important biological function for this measurement modality to prove useful to a broader scientific community. In order to do so, results must be highly consistent and require little to no user manipulation to achieve high quality nynerical results that can be combined with other imaging modalities.

Entities:  

Keywords:  cell dynamics; cellular imaging; interference microscopy; optical thickness measurement; phase imaging; polarization interferometry

Year:  2014        PMID: 25309099      PMCID: PMC4189121          DOI: 10.1117/12.2042103

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  18 in total

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Authors:  G E Sommargren
Journal:  Appl Opt       Date:  1981-02-15       Impact factor: 1.980

2.  Absolute measurement of surface roughness.

Authors:  K Creath; J C Wyant
Journal:  Appl Opt       Date:  1990-09-10       Impact factor: 1.980

3.  Pixelated mask spatial carrier phase shifting interferometry algorithms and associated errors.

Authors:  Bradley T Kimbrough
Journal:  Appl Opt       Date:  2006-07-01       Impact factor: 1.980

4.  A new EPI-based dynamic field mapping method: application to retrospective geometrical distortion corrections.

Authors:  Franck Lamberton; Nicolas Delcroix; Denis Grenier; Bernard Mazoyer; Marc Joliot
Journal:  J Magn Reson Imaging       Date:  2007-09       Impact factor: 4.813

5.  Interference microscopy and mass determination.

Authors:  H G DAVIES; M H F WILKINS
Journal:  Nature       Date:  1952-03-29       Impact factor: 49.962

6.  Measurement of mass, density, and volume during the cell cycle of yeast.

Authors:  Andrea K Bryan; Alexi Goranov; Angelika Amon; Scott R Manalis
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-23       Impact factor: 11.205

7.  Shortest path refinement for motion estimation from tagged MR images.

Authors:  Xiaofeng Liu; Jerry L Prince
Journal:  IEEE Trans Med Imaging       Date:  2010-03-18       Impact factor: 10.048

8.  Using buoyant mass to measure the growth of single cells.

Authors:  Michel Godin; Francisco Feijó Delgado; Sungmin Son; William H Grover; Andrea K Bryan; Amit Tzur; Paul Jorgensen; Kris Payer; Alan D Grossman; Marc W Kirschner; Scott R Manalis
Journal:  Nat Methods       Date:  2010-04-11       Impact factor: 28.547

9.  Dynamic quantitative phase imaging for biological objects using a pixelated phase mask.

Authors:  Katherine Creath; Goldie Goldstein
Journal:  Biomed Opt Express       Date:  2012-10-17       Impact factor: 3.732

10.  CellProfiler: image analysis software for identifying and quantifying cell phenotypes.

Authors:  Anne E Carpenter; Thouis R Jones; Michael R Lamprecht; Colin Clarke; In Han Kang; Ola Friman; David A Guertin; Joo Han Chang; Robert A Lindquist; Jason Moffat; Polina Golland; David M Sabatini
Journal:  Genome Biol       Date:  2006-10-31       Impact factor: 13.583

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