Reliable computational quantification of liver fibrosis is compromised by inherent staining variation-Reference-Cited by-同舟云学术

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Reliable computational quantification of liver fibrosis is compromised by inherent staining variation

Published:2021-06-02 Issue:5 Volume:7 Page:471-481
ISSN:2056-4538
Container-title:The Journal of Pathology: Clinical Research
language:en
Short-container-title:J Pathol Clin Res

Author:

Astbury Stuart¹²^ORCID,Grove Jane I¹²,Dorward David A³⁴^ORCID,Guha Indra N¹²,Fallowfield Jonathan A³,Kendall Timothy J³⁴^ORCID

Affiliation:

1. NIHR Nottingham Biomedical Research Centre Nottingham University Hospitals NHS Trust and the University of Nottingham Nottingham UK

2. Nottingham Digestive Diseases Centre, School of Medicine University of Nottingham Nottingham UK

3. University of Edinburgh Centre for Inflammation Research University of Edinburgh Edinburgh UK

4. Edinburgh Pathology University of Edinburgh Edinburgh UK

Funder

Medical Research Council Canada

Publisher

Wiley

Subject

Pathology and Forensic Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cjp2.227

Reference30 articles.

1. An appraisal of the histopathological assessment of liver fibrosis

2. Sirius Red histophotometry and spectrophotometry of sections in the assessment of the collagen content of liver tissue and its application in growing rat liver

3. Intraobserver and Interobserver Variations in Liver Biopsy Interpretation in Patients with Chronic Hepatitis C

4. Colour perception in pathologists: the Farnsworth-Munsell 100-hue test.

5. Progression of fibrosis in advanced chronic hepatitis C: Evaluation by morphometric image analysis

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2. The Quantification of Myocardial Fibrosis on Human Histopathology Images by a Semi-Automatic Algorithm;Applied Sciences;2024-08-31

3. AI Digital Pathology Using qFibrosis Shows Heterogeneity of Fibrosis Regression in Patients with Chronic Hepatitis B and C with Viral Response;Diagnostics;2024-08-22

4. Outcome prediction in metabolic dysfunction‐associated steatotic liver disease using stain‐free digital pathological assessment;Liver International;2024-08-07

5. Second harmonic generation digital pathology with artificial intelligence: breakthroughs in studying fibrosis dynamics and treatment response;Future Medicine AI;2024-08-05

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