Evidence map›Paper›PMID 27532012›Full record

ArticleIFMBE proceedings

A High-Resolution Tile-Based Approach for Classifying Biological Regions in Whole-Slide Histopathological Images.

R A Hoffman, S Kothari, J H Phan, M D Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IFMBE proceedings. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Detection of blur artifacts in histopathological whole-slide images of endomyocardial biopsies.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2015
    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

4 authors.

R A HoffmanDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
S KothariDepartment of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
J H PhanDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
M D WangDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA; Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA; Winship Cancer Institute, Parker H. Petit Institute of Bioengineering and Biosciences, Institute of People and Technology, Georgia Institute of Technology and Emory University, Atlanta, GA.

Funding

Tissue and Animal UseU54CA119338 · NCI · EMORY UNIVERSITY · PI SHIN, DONG M · 2005 to 2009
$18.4M
Contrast-Enhanced and Image-Guided Surgery of Lung CancerR01CA163256 · NCI · EMORY UNIVERSITY · PI JO, HANJOONG, SINGHAL, SUNIL · 2011 to 2015
$6.5M
Nanotechnology for Multiplexed and Intraoperative Cancer DetectionRC2CA148265 · NCI · EMORY UNIVERSITY · PI NIE, SHUMING · 2009 to 2010
$2.0M
NCI NIH HHS R01 CA163256NCI NIH HHS RC2 CA148265NCI NIH HHS U54 CA119338
6 · The paper itself

Abstract

Computational analysis of histopathological whole slide images (WSIs) has emerged as a potential means for improving cancer diagnosis and prognosis. However, an open issue relating to the automated processing of WSIs is the identification of biological regions such as tumor, stroma, and necrotic tissue on the slide. We develop a method for classifying WSI portions (512x512-pixel tiles) into biological regions by (1) extracting a set of 461 image features from each WSI tile, (2) optimizing tile-level prediction models using nested cross-validation on a small (600 tile) manually annotated tile-level training set, and (3) validating the models against a much larger (1.7x10

Identifiers

PMID27532012
PMCPMC4983443

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Registered trials

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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.