Evidence map›Paper›PMID 30533276›Full record

ArticleJournal of pathology informatics2018

Implementing the DICOM Standard for Digital Pathology.

Markus D Herrmann, David A Clunie, Andriy Fedorov, Sean W Doyle, Steven Pieper, Veronica Klepeis, Long P Le, George L Mutter, David S Milstone, Thomas J Schultz and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of pathology informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

71 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Trial
  3. Review
  4. A Unified Deep Learning Framework for Instance Segmentation Across Diverse Cytological Stains.Cytopathology : official journal of the British Society for Clinical Cytology · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Report on the 2025 DICOM WSI Connectathon.Journal of pathology informatics · 2026
    Article
  11. The evolving role of DICOM in digital pathology.Journal of pathology informatics · 2026
    Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article

11 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Markus D HerrmannMGH and BWH Center for Clinical Data Science, Boston, MA, USA.
David A CluniePixelMed Publishing, LLC, Bangor, PA, USA.
Andriy FedorovDepartment of Radiology, Surgical Planning Laboratory, Brigham and Women's Hospital, Boston, MA, USA.
Sean W DoyleMGH and BWH Center for Clinical Data Science, Boston, MA, USA.
Steven PieperIsomics, Inc., Cambridge, MA, USA.
Veronica KlepeisHarvard Medical School, Boston, MA, USA.
Long P LeHarvard Medical School, Boston, MA, USA.
George L MutterHarvard Medical School, Boston, MA, USA.
David S MilstoneHarvard Medical School, Boston, MA, USA.
Thomas J SchultzEnterprise Medical Imaging, Massachusetts General Hospital, Boston, MA, USA.
Ron KikinisDepartment of Radiology, Surgical Planning Laboratory, Brigham and Women's Hospital, Boston, MA, USA.
Gopal K KotechaMGH and BWH Center for Clinical Data Science, Boston, MA, USA.
David H HwangHarvard Medical School, Boston, MA, USA.
Katherine P AndrioleMGH and BWH Center for Clinical Data Science, Boston, MA, USA.
A John IafrateHarvard Medical School, Boston, MA, USA.
James A BrinkHarvard Medical School, Boston, MA, USA.
Giles W BolandHarvard Medical School, Boston, MA, USA.
Keith J DreyerMGH and BWH Center for Clinical Data Science, Boston, MA, USA.
Mark MichalskiMGH and BWH Center for Clinical Data Science, Boston, MA, USA.
Jeffrey A GoldenHarvard Medical School, Boston, MA, USA.
David N LouisHarvard Medical School, Boston, MA, USA.
Jochen K LennerzHarvard Medical School, Boston, MA, USA.

Funding

Training and DisseminationP41EB015902 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI PUJOL, SONIA · 2012 to 2022
$20.9M
Image Guided Therapy Center - Ultrasound-based sensor system for the monitoring of COVID-19 patientsP41EB015898 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI TEMPANY, CLARE M · 2012 to 2021
$18.9M
Quantitative Image Informatics for Cancer Research (QIICR)U24CA180918 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI FEDOROV, ANDRIY, KIKINIS, RON · 2013 to 2017
$4.0M
NCI NIH HHS U24 CA180918NIBIB NIH HHS P41 EB015898NIBIB NIH HHS P41 EB015902
6 · The paper itself

Abstract

backgroundDigital Imaging and Communications in Medicine (DICOM

methodsWe selected relevant DICOM attributes, developed a program that extracts pixel data and pixel-related metadata, integrated patient and specimen-related metadata, populated and encoded DICOM attributes, and stored DICOM files. We generated the files using image data from four vendor-specific image file formats and clinical metadata from two departments with different laboratory information systems. We validated the generated DICOM files using recognized DICOM validation tools and measured encoding, storage, and access efficiency for three image compression methods. Finally, we evaluated storing, querying, and retrieving data over the web using existing DICOM archive software.

resultsWhole slide image data can be encoded together with relevant patient and specimen-related metadata as DICOM objects. These objects can be accessed efficiently from files or through RESTful web services using existing software implementations. Performance measurements show that the choice of image compression method has a major impact on data access efficiency. For lossy compression, JPEG achieves the fastest compression/decompression rates. For lossless compression, JPEG-LS significantly outperforms JPEG 2000 with respect to data encoding and decoding speed.

conclusionImplementation of DICOM allows efficient access to image data as well as associated metadata. By leveraging a wealth of existing infrastructure solutions, the use of DICOM facilitates enterprise integration and data exchange for digital pathology.

Indexed as

Computational pathologyDICOMwebimage compressionslide scanningwhole slide imaging

Identifiers

PMID30533276
PMCPMC6236926

What Socratic holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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 Socratic graph.