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Editorial
. 2022 Feb 11;3(3):413-415.
doi: 10.34067/KID.0007982021. eCollection 2022 Mar 31.

How Whole Slide Imaging and Machine Learning Can Partner with Renal Pathology

Parker C Wilson  1 , Nidia Messias
Affiliations
Editorial

How Whole Slide Imaging and Machine Learning Can Partner with Renal Pathology

Parker C Wilson et al. Kidney360. .
No abstract available

Keywords: basic science; digital image analysis; glomerular and tubulointerstitial diseases; machine learning; membranous nephropathy; minimal change disease; renal pathology; thin basement membrane disease; whole slide imaging.

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Conflict of interest statement

All authors have nothing to disclose.

Figures

Figure 1.
Figure 1.
Integration of whole slide imaging and digital image analysis into a renal pathology workflow. Kidney biopsy tissue is subdivided and prepared for light microscopy, immunofluorescence microscopy, and electron microscopy. High-throughput slide scanners are used to generate whole slide images from the slides prepared for light microscopy. Digital image analysis algorithms interrogate features within whole slide images to generate a report for the renal pathologist. This report could include tissue-based metrics such as the number of sclerotic glomeruli, proportion of interstitial fibrosis, estimates of podocyte depletion, or even suggest a potential diagnosis. The digital imaging analysis report is used in combination with traditional light, immunofluorescence, and electron microscopy to make an integrated diagnosis.
See this image and copyright information in PMC

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References

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