Literature DB >> 30847052

Multispectral analysis tools can increase utility of RGB color images in histology.

Farzad Fereidouni1, Croix Griffin2, Austin Todd1, Richard Levenson1.   

Abstract

Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

Entities:  

Keywords:  fluorescence; histopathology; phasor analysis; spectral imaging

Year:  2018        PMID: 30847052      PMCID: PMC6398595          DOI: 10.1088/2040-8986/aab0e8

Source DB:  PubMed          Journal:  J Opt        ISSN: 2040-8978            Impact factor:   2.516


  32 in total

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Authors:  H C Gerritsen; M A H Asselbergs; A V Agronskaia; W G J H M Van Sark
Journal:  J Microsc       Date:  2002-06       Impact factor: 1.758

2.  Optimizing imaging parameters for the separation of multiple labels in a fluorescence image.

Authors:  R Neher; E Neher
Journal:  J Microsc       Date:  2004-01       Impact factor: 1.758

3.  Use of a multi-spectral camera in the characterization of skin wounds.

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Journal:  Opt Express       Date:  2010-02-15       Impact factor: 3.894

4.  Hyperspectral confocal microscope.

Authors:  Michael B Sinclair; David M Haaland; Jerilyn A Timlin; Howland D T Jones
Journal:  Appl Opt       Date:  2006-08-20       Impact factor: 1.980

5.  Spectral imaging perspective on cytomics.

Authors:  Richard M Levenson
Journal:  Cytometry A       Date:  2006-07       Impact factor: 4.355

6.  Reliable cell segmentation based on spectral phasor analysis of hyperspectral stimulated Raman scattering imaging data.

Authors:  Dan Fu; X Sunney Xie
Journal:  Anal Chem       Date:  2014-04-08       Impact factor: 6.986

7.  The fluorescent staining of heparin in mast cells using berberine sulfate: compatibility with paraformaldehyde or o-phthalaldehyde induced fluorescence and metachromasia.

Authors:  R V Dimlich; H A Meineke; F D Reilly; R S McCuskey
Journal:  Stain Technol       Date:  1980-07

8.  Canine cutaneous mast cell tumor: morphologic grading and survival time in 83 dogs.

Authors:  A K Patnaik; W J Ehler; E G MacEwen
Journal:  Vet Pathol       Date:  1984-09       Impact factor: 2.221

9.  In vivo monitoring of protein-bound and free NADH during ischemia by nonlinear spectral imaging microscopy.

Authors:  Jonathan A Palero; Arjen N Bader; Henriëtte S de Bruijn; Angélique van der Ploeg van den Heuvel; Henricus J C M Sterenborg; Hans C Gerritsen
Journal:  Biomed Opt Express       Date:  2011-04-01       Impact factor: 3.732

10.  Spatial computation of intratumoral T cells correlates with survival of patients with pancreatic cancer.

Authors:  Julienne L Carstens; Pedro Correa de Sampaio; Dalu Yang; Souptik Barua; Huamin Wang; Arvind Rao; James P Allison; Valerie S LeBleu; Raghu Kalluri
Journal:  Nat Commun       Date:  2017-04-27       Impact factor: 14.919

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  5 in total

1.  Dual-mode emission and transmission microscopy for virtual histochemistry using hematoxylin- and eosin-stained tissue sections.

Authors:  Farzad Fereidouni; Austin Todd; Yuheng Li; Che-Wei Chang; Keith Luong; Avi Rosenberg; Yong-Jae Lee; James W Chan; Alexander Borowsky; Karen Matsukuma; Kuang-Yu Jen; Richard Levenson
Journal:  Biomed Opt Express       Date:  2019-11-26       Impact factor: 3.732

Review 2.  Live-cell fluorescence spectral imaging as a data science challenge.

Authors:  Jessy Pamela Acuña-Rodriguez; Jean Paul Mena-Vega; Orlando Argüello-Miranda
Journal:  Biophys Rev       Date:  2022-03-23

Review 3.  Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples.

Authors:  Alton B Farris; Juan Vizcarra; Mohamed Amgad; Lee A D Cooper; David Gutman; Julien Hogan
Journal:  Histopathology       Date:  2021-03-08       Impact factor: 5.087

4.  Spectroscopic and deep learning-based approaches to identify and quantify cerebral microhemorrhages.

Authors:  Christian Crouzet; Gwangjin Jeong; Rachel H Chae; Krystal T LoPresti; Cody E Dunn; Danny F Xie; Chiagoziem Agu; Chuo Fang; Ane C F Nunes; Wei Ling Lau; Sehwan Kim; David H Cribbs; Mark Fisher; Bernard Choi
Journal:  Sci Rep       Date:  2021-05-21       Impact factor: 4.379

5.  Banff Digital Pathology Working Group: Going digital in transplant pathology.

Authors:  Alton B Farris; Ishita Moghe; Simon Wu; Julien Hogan; Lynn D Cornell; Mariam P Alexander; Jesper Kers; Anthony J Demetris; Richard M Levenson; John Tomaszewski; Laura Barisoni; Yukako Yagi; Kim Solez
Journal:  Am J Transplant       Date:  2020-04-19       Impact factor: 8.086

  5 in total

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