Evidence map›Paper›PMID 22257649›Full record

ArticleComputer methods and programs in biomedicine2012

Creating a virtual slide map from sputum smear images for region-of-interest localisation in automated microscopy.

Bhavin Patel, Tania S Douglas

Abstract read
In one paragraph

Article in Computer methods and programs in biomedicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Clinical microbiology informatics.Clinical microbiology reviews · 2014
    Review
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

2 authors.

Bhavin PatelMRC/UCT Medical Imaging Research Unit, Department of Human Biology, University of Cape Town, Observatory 7925, Cape Town, South Africa.
Tania S Douglas

Funding

A smart microscope for the detection of tuberculosis in ZN-stained sputum smearsR21AI067659 · NIAID · UNIVERSITY OF CAPE TOWN · PI DOUGLAS, TANIA S · 2007 to 2008
$294k
NIAID NIH HHS R21 AI067659NIAID NIH HHS R21 AI067659-01A2.
6 · The paper itself

Abstract

We address the location of regions-of-interest in previously scanned sputum smear slides requiring re-examination in automated microscopy for tuberculosis (TB) detection. We focus on the core component of microscope auto-positioning, which is to find a point of reference, position and orientation, on the slide so that it can be used to automatically bring desired fields to the field-of-view of the microscope. We use virtual slide maps together with geometric hashing to localise a query image, which then acts as the point of reference. The true positive rate achieved by the algorithm was above 88% even for noisy query images captured at slide orientations up to 26°. The image registration error, computed as the average mean square error, was less than 14 pixel² (corresponding to 1.02 μm²). The algorithm is inherently robust to changes in slide orientation and placement and showed high tolerance to illumination changes and robustness to noise.

Indexed as

AutomationSputumAlgorithmsHumansMicroscopy

Identifiers

PMID22257649
PMCPMC3350602

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.