Evidence map›Paper›PMID 28331891›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2017

Differentiation of arterioles from venules in mouse histology images using machine learning.

J Sachi Elkerton, Yiwen Xu, J Geoffrey Pickering, Aaron D Ward

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 28% of its field
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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. 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 at 1 institution in 1 country.

J Sachi ElkertonWestern University, Department of Medical Biophysics, 1151 Richmond Street, London, Ontario N6A 3K7, Canada; Baines Imaging Research Laboratory, London Regional Cancer Program, 800 Commissioners Road East, London, Ontario N6A 5W9, Canada.
Yiwen XuWestern University, Department of Medical Biophysics, 1151 Richmond Street, London, Ontario N6A 3K7, Canada; Baines Imaging Research Laboratory, London Regional Cancer Program, 800 Commissioners Road East, London, Ontario N6A 5W9, Canada; Western University, Robarts Research Institute, 1151 Richmond Street, London, Ontario N6A 3K7, Canada.
J Geoffrey PickeringWestern University, Department of Medical Biophysics, 1151 Richmond Street, London, Ontario N6A 3K7, Canada; Western University, Robarts Research Institute, 1151 Richmond Street, London, Ontario N6A 3K7, Canada.
Aaron D WardWestern University, Department of Medical Biophysics, 1151 Richmond Street, London, Ontario N6A 3K7, Canada; Baines Imaging Research Laboratory, London Regional Cancer Program, 800 Commissioners Road East, London, Ontario N6A 5W9, Canada.
Western University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analysis and morphological comparison of the arteriolar and venular components of a microvascular network are essential to our understanding of multiple diseases affecting every organ system. We have developed and evaluated the first fully automatic software system for differentiation of arterioles from venules on high-resolution digital histology images of the mouse hind limb immunostained with smooth muscle [Formula: see text]-actin. Classifiers trained on statistical and morphological features by supervised machine learning provided useful classification accuracy for differentiation of arterioles from venules, achieving an area under the receiver operating characteristic curve of 0.89. Feature selection was consistent across cross validation iterations, and a small set of two features was required to achieve the reported performance, suggesting the generalizability of the system. This system eliminates the need for laborious manual classification of the hundreds of microvessels occurring in a typical sample and paves the way for high-throughput analysis of the arteriolar and venular networks in the mouse.

Indexed as

arteriole venule classificationfeature analysismachine learningvasculature quantificationwhole slide analysis

Identifiers

PMID28331891
PMCPMC5330885
OpenAlexW2594785967

What OpenQuestion holds

Textmetadata
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.