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Whole slide image data utilization informed by digital diagnosis patterns

Kimberly Ashman, Huimin Zhuge, Erin Shanley, Sharon Fox, Shams Halat, Andrew B. Sholl, Brian Summa, J. Quincy Brown

2022Journal of Pathology Informatics13 citationsDOIOpen Access PDF

Abstract

Context: Despite the benefits of digital pathology, data storage and management of digital whole slide images introduces new logistical and infrastructure challenges to traditionally analog pathology labs. Aims: Our goal was to analyze pathologist slide diagnosis patterns to determine the minimum number of pixels required during the diagnosis. Methods: We developed a method of using pathologist viewing patterns to vary digital image resolution across virtual slides, which we call variable resolution images. An additional pathologist reviewed the variable resolution images to determine if diagnoses could still be rendered. Results: Across all slides, the pathologists rarely zoomed in to the full resolution level. As a result, the variable resolution images are significantly smaller than the original whole slide images. Despite the reduction in image sizes, the final pathologist reviewer could still proide diagnoses on the variable resolution slide images. Conclusions: Future studies will be conducted to understand variability in resolution requirements between and within pathologists. These findings have the potential to dramatically reduce the data storage requirements of high-resolution whole slide images.

Topics & Concepts

Computer scienceDigital pathologyInformation retrievalData scienceDigital imageData miningImage (mathematics)Computer graphics (images)MultimediaWorld Wide WebArtificial intelligenceImage processingAI in cancer detectionRadiology practices and educationDigital Radiography and Breast Imaging
Whole slide image data utilization informed by digital diagnosis patterns | Litcius