ReviewJournal of pathology informatics2013
Relationship between magnification and resolution in digital pathology systems.
Review in Journal of pathology informatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- Whole-slide imaging in hematopathology: Current state, challenges and future opportunities.Journal of pathology informatics · 2026Review
- Improving cellular nuclei detection in histological images by combining super-resolution techniques and deep learning-based object detectors.Medical & biological engineering & computing · 2026Article
- Comparative analysis of whole-slide scanner tissue detection algorithms: Implications for scan area, scan time, and file size in high-volume digital pathology workflows.Journal of pathology informatics · 2026Article
- Risk Classification of Low-Resolution Whole-Slide Thumbnail Images by Multi-dimensional Feature Reconstruction with Multi-task Deep Learning Network Helps Prioritize Pathology Case Registration.Journal of imaging informatics in medicine · 2026Article
- Label-free whole slide virtual multi-staining using dual-excitation photon absorption remote sensing microscopy.Npj imaging · 2026Article
- Deep Learning Classification of Prostate Cancer Using MRI Histopathologic Data.Radiology. Imaging cancer · 2025Article
- Digital slide scanning at scale: Comparison of whole slide imaging devices in a clinical setting.Journal of pathology informatics · 2025Article
- Smart neural network and cognitive computing process for multi task nuclei detection segmentation and classification in breast cancer histopathology images.Scientific reports · 2025Article
- GNCnn: A QuPath extension for glomerulosclerosis and glomerulonephritis characterization based on deep learning.Computational and structural biotechnology journal · 2025Article
- Whole Slide Images in Artificial Intelligence Applications in Digital Pathology: Challenges and Pitfalls.Turk patoloji dergisi · 2023Article
- Hagnifinder: Recovering magnification information of digital histological images using deep learning.Journal of pathology informatics · 2023Article
- Defining the area of mitoses counting in invasive breast cancer using whole slide image.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2022Article
- Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies.Nature medicine · 2022Article
- Slide Over: Advances in Slide-Free Optical Microscopy as Drivers of Diagnostic Pathology.The American journal of pathology · 2022Review
- Software tools and platforms in Digital Pathology: a review for clinicians and computer scientists.Journal of pathology informatics · 2022Review
- Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Digital Versus Optical Diagnosis of Follicular Patterned Thyroid Lesions.Head and neck pathology · 2021Article
- Contemporary Whole Slide Imaging Devices and Their Applications within the Modern Pathology Department: A Selected Hardware Review.Journal of pathology informatics · 2021Review
- Texture features in the Shearlet domain for histopathological image classification.BMC medical informatics and decision making · 2020Article
- (Re) Defining the High-Power Field for Digital Pathology.Journal of pathology informatics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many pathology laboratories are implementing digital pathology systems. The image resolution and scanning (digitization) magnification can vary greatly between these digital pathology systems. In addition, when digital images are compared with viewing images using a microscope, the cellular features can vary in size. This article highlights differences in magnification and resolution between the conventional microscopes and the digital pathology systems. As more pathologists adopt digital pathology, it is important that they understand these differences and how they ultimately translate into what the pathologist can see and how this may impact their overall viewing experience.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.