Literature DB >> 21370029

Practical considerations of image analysis and quantification of signal transduction IHC staining.

Michael Grunkin1, Jakob Raundahl, Niels T Foged.   

Abstract

The dramatic increase in computer processing power in combination with the availability of high-quality digital cameras during the last 10 years has fertilized the grounds for quantitative microscopy based on digital image analysis. With the present introduction of robust scanners for whole slide imaging in both research and routine, the benefits of automation and objectivity in the analysis of tissue sections will be even more obvious. For in situ studies of signal transduction, the combination of tissue microarrays, immunohistochemistry, digital imaging, and quantitative image analysis will be central operations. However, immunohistochemistry is a multistep procedure including a lot of technical pitfalls leading to intra- and interlaboratory variability of its outcome. The resulting variations in staining intensity and disruption of original morphology are an extra challenge for the image analysis software, which therefore preferably should be dedicated to the detection and quantification of histomorphometrical end points.

Mesh:

Year:  2011        PMID: 21370029     DOI: 10.1007/978-1-61779-024-9_8

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  8 in total

1.  Forkhead box protein O1 (FOXO1) and paired box gene 3 (PAX3) overexpression is associated with poor prognosis in patients with cervical cancer.

Authors:  Doo Byung Chay; Gwan Hee Han; Sanghee Nam; Hanbyoul Cho; Joon-Yong Chung; Stephen M Hewitt
Journal:  Int J Clin Oncol       Date:  2019-07-13       Impact factor: 3.402

2.  Overexpression of glucocorticoid receptor promotes the poor progression and induces cisplatin resistance through p38 MAP kinase in cervical cancer patients.

Authors:  Gwan Hee Han; Hee Yun; Julie Kim; Joon-Yong Chung; Jae-Hoon Kim; Hanbyoul Cho
Journal:  Am J Cancer Res       Date:  2022-07-15       Impact factor: 5.942

Review 3.  The Use of Quantitative Digital Pathology to Measure Proteoglycan and Glycosaminoglycan Expression and Accumulation in Healthy and Diseased Tissues.

Authors:  A Sally Davis; Mary Y Chang; Jourdan E Brune; Teal S Hallstrand; Brian Johnson; Sarah Lindhartsen; Stephen M Hewitt; Charles W Frevert
Journal:  J Histochem Cytochem       Date:  2020-09-16       Impact factor: 2.479

4.  Robust extraction of quantitative structural information from high-variance histological images of livers from necropsied Soay sheep.

Authors:  Q Caudron; R Garnier; J G Pilkington; K A Watt; C Hansen; B T Grenfell; T Aboellail; A L Graham
Journal:  R Soc Open Sci       Date:  2017-07-19       Impact factor: 2.963

5.  A texture based pattern recognition approach to distinguish melanoma from non-melanoma cells in histopathological tissue microarray sections.

Authors:  Elton Rexhepaj; Margrét Agnarsdóttir; Julia Bergman; Per-Henrik Edqvist; Michael Bergqvist; Mathias Uhlén; William M Gallagher; Emma Lundberg; Fredrik Ponten
Journal:  PLoS One       Date:  2013-05-17       Impact factor: 3.240

6.  Decreased apoptotic rate of alveolar macrophages of patients with idiopathic pulmonary fibrosis.

Authors:  Fotios Drakopanagiotakis; Areti Xifteri; Evaggelos Tsiambas; Andreas Karameris; Konstantina Tsakanika; Napoleon Karagiannidis; Demetrios Mermigkis; Vlasis Polychronopoulos; Demosthenes Bouros
Journal:  Pulm Med       Date:  2012-06-25

7.  Prognostic assessment of hypoxia and metabolic markers in cervical cancer using automated digital image analysis of immunohistochemistry.

Authors:  Bo Wook Kim; Hanbyoul Cho; Joon-Yong Chung; Catherine Conway; Kris Ylaya; Jae-Hoon Kim; Stephen M Hewitt
Journal:  J Transl Med       Date:  2013-08-08       Impact factor: 5.531

8.  Analysis of new bone, cartilage, and fibrosis tissue in healing murine allografts using whole slide imaging and a new automated histomorphometric algorithm.

Authors:  Longze Zhang; Martin Chang; Christopher A Beck; Edward M Schwarz; Brendan F Boyce
Journal:  Bone Res       Date:  2016-01-19       Impact factor: 13.567

  8 in total

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