Evidence map›Paper›PMID 24746250›Full record

ReviewComputerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society2015

Evaluating performance of biomedical image retrieval systems--an overview of the medical image retrieval task at ImageCLEF 2004-2013.

Jayashree Kalpathy-Cramer, Alba García Seco de Herrera, Dina Demner-Fushman, Sameer Antani, Steven Bedrick, Henning Müller

Abstract readEvaluation StudyReview
In one paragraph

Review in Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. A Hybrid Rao-NM Algorithm for Image Template Matching.Entropy (Basel, Switzerland) · 2021
    Article
  8. Article
  9. Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines.Journal of the Association for Information Science and Technology · 2019
    Review
  10. Article
  11. Article
  12. Compound image segmentation of published biomedical figures.Bioinformatics (Oxford, England) · 2018
    Article
  13. Article
  14. Article
  15. Preparing a collection of radiology examinations for distribution and retrieval.Journal of the American Medical Informatics Association : JAMIA · 2016
    Article
  16. Article
  17. Article
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

6 authors.

Jayashree Kalpathy-CramerAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: kalpathy@nmr.mgh.harvard.edu.
Alba García Seco de HerreraUniversity of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland.
Dina Demner-FushmanNational Library of Medicine/National Institutes of Health (NLM/NIH), Bethesda, MD, USA.
Sameer AntaniNational Library of Medicine/National Institutes of Health (NLM/NIH), Bethesda, MD, USA.
Steven BedrickOregon Health & Science University, Portland, OR, USA.
Henning MüllerUniversity of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland.

Funding

Integrating image and text information for biomedical information retrieval ZIALM010001 · NLM · NATIONAL LIBRARY OF MEDICINE · PI DEMNER-FUSHMAN, DINA · 2010 to 2020
$6.0M
Quantitative MRI of Glioblastoma ResponseU01CA154601 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI KALPATHY-CRAMER, JAYASHREE · 2011 to 2016
$3.4M
Shutter-Speed Model DCE-MRI for Assessment of Response to Cancer TherapyU01CA154602 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI HUANG, WEI, RYAN, CHRISTOPHER WALTER · 2011 to 2015
$2.9M
Clinical Image Retrieval: User needs assessment toolbox development & evaluationR00LM009889 · NLM · MASSACHUSETTS GENERAL HOSPITAL · PI KALPATHY-CRAMER, JAYASHREE · 2011 to 2013
$690k
NCI NIH HHS U01 CA154601NCI NIH HHS U01 CA154602NCI NIH HHS U01CA154602NLM NIH HHS R00 LM009889NLM NIH HHS R00LM009889
6 · The paper itself

Abstract

Medical image retrieval and classification have been extremely active research topics over the past 15 years. Within the ImageCLEF benchmark in medical image retrieval and classification, a standard test bed was created that allows researchers to compare their approaches and ideas on increasingly large and varied data sets including generated ground truth. This article describes the lessons learned in ten evaluation campaigns. A detailed analysis of the data also highlights the value of the resources created.

Indexed as

Natural Language ProcessingSubtraction TechniqueVocabulary, ControlledAlgorithmsArtificial IntelligenceDocumentationInformation Storage and RetrievalMultimodal ImagingPattern Recognition, AutomatedRadiology Information SystemsTerminology as TopicUser-Computer InterfaceBiomedical literatureContent-based retrievalImage retrievalMultimodal medical retrievalText-based image retrieval

Identifiers

PMID24746250
PMCPMC4177510

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.