Literature DB >> 25863518

Appearance normalization of histology slides.

Jared Vicory1, Heather D Couture1, Nancy E Thomas2, David Borland3, J S Marron4, John Woosley5, Marc Niethammer6.   

Abstract

This paper presents a method for automatic color and intensity normalization of digitized histology slides stained with two different agents. In comparison to previous approaches, prior information on the stain vectors is used in the plane estimation process, resulting in improved stability of the estimates. Due to the prevalence of hematoxylin and eosin staining for histology slides, the proposed method has significant practical utility. In particular, it can be used as a first step to standardize appearance across slides and is effective at countering effects due to differing stain amounts and protocols and counteracting slide fading. The approach is validated against non-prior plane-fitting using synthetic experiments and 13 real datasets. Results of application of the method to adjustment of faded slides are given, and the effectiveness of the method in aiding statistical classification is shown.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Appearance normalization; Histology

Mesh:

Substances:

Year:  2015        PMID: 25863518      PMCID: PMC4769595          DOI: 10.1016/j.compmedimag.2015.03.005

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  2 in total

1.  Quantification of histochemical staining by color deconvolution.

Authors:  A C Ruifrok; D A Johnston
Journal:  Anal Quant Cytol Histol       Date:  2001-08       Impact factor: 0.302

2.  Image and statistical analysis of melanocytic histology.

Authors:  Jayson Miedema; James Stephen Marron; Marc Niethammer; David Borland; John Woosley; Jason Coposky; Susan Wei; Howard Reisner; Nancy E Thomas
Journal:  Histopathology       Date:  2012-06-11       Impact factor: 5.087

  2 in total
  6 in total

1.  Spatial Statistics for Segmenting Histological Structures in H&E Stained Tissue Images.

Authors:  Luong Nguyen; Akif Burak Tosun; Jeffrey L Fine; Adrian V Lee; D Lansing Taylor; S Chakra Chennubhotla
Journal:  IEEE Trans Med Imaging       Date:  2017-03-16       Impact factor: 10.048

2.  Stain Deconvolution Using Statistical Analysis of Multi-Resolution Stain Colour Representation.

Authors:  Najah Alsubaie; Nicholas Trahearn; Shan E Ahmed Raza; David Snead; Nasir M Rajpoot
Journal:  PLoS One       Date:  2017-01-11       Impact factor: 3.240

3.  Image processing in digital pathology: an opportunity to solve inter-batch variability of immunohistochemical staining.

Authors:  Yves-Rémi Van Eycke; Justine Allard; Isabelle Salmon; Olivier Debeir; Christine Decaestecker
Journal:  Sci Rep       Date:  2017-02-21       Impact factor: 4.379

Review 4.  Role of AI and Histopathological Images in Detecting Prostate Cancer: A Survey.

Authors:  Sarah M Ayyad; Mohamed Shehata; Ahmed Shalaby; Mohamed Abou El-Ghar; Mohammed Ghazal; Moumen El-Melegy; Nahla B Abdel-Hamid; Labib M Labib; H Arafat Ali; Ayman El-Baz
Journal:  Sensors (Basel)       Date:  2021-04-07       Impact factor: 3.576

5.  Automated quality assessment of large digitised histology cohorts by artificial intelligence.

Authors:  Maryam Haghighat; Lisa Browning; Korsuk Sirinukunwattana; Stefano Malacrino; Nasullah Khalid Alham; Richard Colling; Ying Cui; Emad Rakha; Freddie C Hamdy; Clare Verrill; Jens Rittscher
Journal:  Sci Rep       Date:  2022-03-23       Impact factor: 4.379

6.  Normalization of HE-stained histological images using cycle consistent generative adversarial networks.

Authors:  Marlen Runz; Daniel Rusche; Stefan Schmidt; Martin R Weihrauch; Jürgen Hesser; Cleo-Aron Weis
Journal:  Diagn Pathol       Date:  2021-08-06       Impact factor: 2.644

  6 in total

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