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The Importance of eSlide Macro Images for Primary Diagnosis with Whole Slide Imaging
- Source :
- Journal of Pathology Informatics, Vol 9, Iss 1, Pp 46-46 (2018)
- Publication Year :
- 2018
-
Abstract
- Introduction: A whole slide image (WSI) is typically comprised of a macro image (low-power snapshot of the entire glass slide) and stacked tiles in a pyramid structure (with the lowest resolution thumbnail at the top). The macro image shows the label and all pieces of tissue on the slide. Many whole slide scanner vendors do not readily show the macro overview to pathologists. We demonstrate that failure to do so may result in a serious misdiagnosis. Materials and Methods: Various examples of errors were accumulated that occurred during the digitization of glass slides where the virtual slide differed from the macro image of the original glass slide. Such examples were retrieved from pathology laboratories using different types of scanners in the USA, Canada, Europe, and Asia. Results: The reasons for image errors were categorized into technical problems (e.g., automatic tissue finder failure, image mismatches, and poor scan coverage) and human operator mistakes (e.g., improper manual region of interest selection). These errors were all detected because they were highlighted in the macro image. Conclusion: Our experience indicates that WSI can be subject to inadvertent errors related to glitches in scanning slides, corrupt images, or mistakes made by humans when scanning slides. Displaying the macro image that accompanies WSIs is critical from a quality control perspective in digital pathology practice as this can help detect these serious image-related problems and avoid compromised diagnoses.
- Subjects :
- Scanner
thumbnail
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Health Informatics
lcsh:Computer applications to medicine. Medical informatics
macro image
030218 nuclear medicine & medical imaging
Pathology and Forensic Medicine
03 medical and health sciences
0302 clinical medicine
Region of interest
lcsh:Pathology
Digital pathology
informatics
Computer vision
Macro
Virtual slide
Digitization
business.industry
Thumbnail
error
whole slide imaging
Computer Science Applications
030220 oncology & carcinogenesis
Whole slide image
lcsh:R858-859.7
Artificial intelligence
business
lcsh:RB1-214
Subjects
Details
- ISSN :
- 22295089
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Journal of pathology informatics
- Accession number :
- edsair.doi.dedup.....fcc4af59fc78e4b5693f1a4145b4c216