ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2015
Detection of blur artifacts in histopathological whole-slide images of endomyocardial biopsies.
Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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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.
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Who cites it
8 citing papers in PubMed.
- Longitudinal evaluation of tumor-infiltrating lymphocyte scoring using automated region of interest registration in breast cancer.Breast cancer research : BCR · 2026Article
- A robust and scalable framework for hallucination detection in virtual tissue staining and digital pathology.Nature biomedical engineering · 2025Article
- Deep learning for digital pathology: A critical overview of methodological framework.Journal of pathology informatics · 2025Review
- Machine learning methods for histopathological image analysis: Updates in 2024.Computational and structural biotechnology journal · 2025Review
- [Artificial intelligence for pathology-how, where, and why?]Pathologie (Heidelberg, Germany) · 2024Article
- Preparing Data for Artificial Intelligence in Pathology with Clinical-Grade Performance.Diagnostics (Basel, Switzerland) · 2023Review
- Automated quality assessment of large digitised histology cohorts by artificial intelligence.Scientific reports · 2022Article
- Machine Learning Methods for Histopathological Image Analysis.Computational and structural biotechnology journal · 2018Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Histopathological whole-slide images (WSIs) have emerged as an objective and quantitative means for image-based disease diagnosis. However, WSIs may contain acquisition artifacts that affect downstream image feature extraction and quantitative disease diagnosis. We develop a method for detecting blur artifacts in WSIs using distributions of local blur metrics. As features, these distributions enable accurate classification of WSI regions as sharp or blurry. We evaluate our method using over 1000 portions of an endomyocardial biopsy (EMB) WSI. Results indicate that local blur metrics accurately detect blurry image regions.
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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.