ArticleJournal of digital imaging2022
Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology.
Article in Journal of digital imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- A Whole-Body PSMA-PET/CT dataset with manually annotated tumor lesions.Scientific data · 2026Article
- Contrastive virtual staining enhances deep learning-based PDAC subtyping from H&E-stained tissue cores.The Journal of pathology · 2026Article
- Deep Learning Applications in Clinical Cancer Detection: A Review of Implementation Challenges and Solutions.Mayo Clinic proceedings. Digital health · 2025Review
- Multi-modal dataset creation for federated learning with DICOM-structured reports.International journal of computer assisted radiology and surgery · 2025Article
- Application of machine learning-based multi-sequence MRI radiomics in diagnosing anterior cruciate ligament tears.Journal of orthopaedic surgery and research · 2024Article
- Enrichment of lung cancer computed tomography collections with AI-derived annotations.Scientific data · 2024Article
- National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence.Radiographics : a review publication of the Radiological Society of North America, Inc · 2023Article
- HistoMIL: A Python package for training multiple instance learning models on histopathology slides.iScience · 2023Article
- Thirty Years of the DICOM Standard.Tomography (Ann Arbor, Mich.) · 2023Review
- Machine and Deep Learning Dominate Recent Innovations in Sensors, Signals and Imaging Informatics.Yearbook of medical informatics · 2023Review
- Interoperable slide microscopy viewer and annotation tool for imaging data science and computational pathology.Nature communications · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Machine learning (ML) is revolutionizing image-based diagnostics in pathology and radiology. ML models have shown promising results in research settings, but the lack of interoperability between ML systems and enterprise medical imaging systems has been a major barrier for clinical integration and evaluation. The DICOM
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.