Evidence map›Paper›PMID 25919426›Full record

ArticleJournal of biomedical optics2015

Automated frame selection process for high-resolution microendoscopy.

Ayumu Ishijima, Richard A Schwarz, Dongsuk Shin, Sharon Mondrik, Nadarajah Vigneswaran, Ann M Gillenwater, Sharmila Anandasabapathy, Rebecca Richards-Kortum

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Cancer prevention research (Philadelphia, Pa.) · 2018
    Trial
  2. Article
  3. Article
  4. Review
  5. Article
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  7. Review
  8. Article
  9. Article
  10. Differential structured illumination microendoscopy for in vivo imaging of molecular contrast agents.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Article
  11. 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

8 authors.

Ayumu IshijimaRice University, Department of Bioengineering MS 142, 6100 Main Street, Houston, Texas 77005, United StatesbUniversity of Tokyo, Department of Precision Engineering, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
Richard A SchwarzRice University, Department of Bioengineering MS 142, 6100 Main Street, Houston, Texas 77005, United States.
Dongsuk ShinRice University, Department of Bioengineering MS 142, 6100 Main Street, Houston, Texas 77005, United States.
Sharon MondrikRice University, Department of Bioengineering MS 142, 6100 Main Street, Houston, Texas 77005, United States.
Nadarajah VigneswaranUniversity of Texas School of Dentistry, 7500 Cambridge Street, Houston, Texas 77054, United States.
Ann M GillenwaterUniversity of Texas M. D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States.
Sharmila AnandasabapathyMount Sinai Medical Center, Division of Gastroenterology, One Gustave L. Levy Place, New York, New York 10029, United States.
Rebecca Richards-KortumRice University, Department of Bioengineering MS 142, 6100 Main Street, Houston, Texas 77005, United States.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Kathrin Milbury · 1985 to 2026
$290.8M
Integrated Optical Needle (ION) for Cellular and Molecular Imaging of CancerR01EB007594 · NIBIB · RICE UNIVERSITY · PI RICHARDS-KORTUM, REBECCA R. · 2008 to 2011
$1.6M
High Resolution Microendoscopy for the Detection of Esophageal NeoplasiaR21CA156704 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ANANDASABAPATHY, SHARMILA, RICHARDS-KORTUM, REBECCA R. · 2011 to 2012
$697k
NCI NIH HHS P30 CA016672NCI NIH HHS R21 CA156704NCI NIH HHS R21CA156704NIBIB NIH HHS R01 EB007594NIBIB NIH HHS R01EB007594
6 · The paper itself

Abstract

We developed an automated frame selection algorithm for high-resolution microendoscopy video sequences. The algorithm rapidly selects a representative frame with minimal motion artifact from a short video sequence, enabling fully automated image analysis at the point-of-care. The algorithm was evaluated by quantitative comparison of diagnostically relevant image features and diagnostic classification results obtained using automated frame selection versus manual frame selection. A data set consisting of video sequences collected in vivo from 100 oral sites and 167 esophageal sites was used in the analysis. The area under the receiver operating characteristic curve was 0.78 (automated selection) versus 0.82 (manual selection) for oral sites, and 0.93 (automated selection) versus 0.92 (manual selection) for esophageal sites. The implementation of fully automated high-resolution microendoscopy at the point-of-care has the potential to reduce the number of biopsies needed for accurate diagnosis of precancer and cancer in low-resource settings where there may be limited infrastructure and personnel for standard histologic analysis.

Indexed as

Endoscopy, GastrointestinalEsophageal NeoplasmsEsophagusHumansImage Processing, Computer-AssistedMicroscopyROC Curve

Identifiers

PMID25919426
PMCPMC4412137

What OpenQuestion holds

Textmetadata
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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.