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February 9, 2026Physica Medica0 citationsOpen Access

Ensuring reliable digital pathology: a comparative analysis of HistoQC and PathProfiler for artefacts detection in prostate whole-slide images

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DRDaniele RavanelliERErich RobbiSCSara Citter

Key Points

  • The central aim is to compare HistoQC and PathProfiler for detecting artefacts in whole-slide images of prostate cancer.
  • Conducted a comparative analysis of HistoQC and PathProfiler.
  • Evaluated their reliability in assessing whole-slide image quality.
  • Assessed adaptability of HistoQC using machine learning techniques.
  • Both tools reliably assess whole-slide image quality in prostate cancer.
  • PathProfiler shows greater efficiency for clinical use compared to HistoQC.
  • HistoQC offers adaptable scoring which enhances diagnostic accuracy.

Abstract

HistoQC and PathProfiler reliably assess WSI quality in prostate cancer. PathProfiler offers efficiency for clinical use, while HistoQC provides adaptable scoring via machine learning. Together, they can enhance diagnostic accuracy and support integration of AI in digital pathology workflows.

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Cite This Study

Ravanelli et al. (2026) studied this question.

synapsesocial.com/papers/69897983f0ec2af6756e73c1https://doi.org/10.1016/j.ejmp.2026.105745
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