Evidence map›Paper›PMID 27491802›Full record

ArticleMedical & biological engineering & computing2017

Lens opacity detection for serious posterior subcapsular cataract.

Wanjun Zhang, Huiqi Li

Abstract read
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In one paragraph

Article in Medical & biological engineering & computing, 2017. 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
1.5field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 15 citations in OpenAlex.

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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 at 1 institution in 1 country.

Wanjun ZhangSchool of Information and Electronics, Beijing Institute of Technology, Beijing, 100081, China.
Huiqi LiSchool of Information and Electronics, Beijing Institute of Technology, Beijing, 100081, China. huiqili@bit.edu.cn.
Beijing Institute of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cataract leads to visual impairment. Among different types of cataract, posterior subcapsular cataract (PSC) can develop rapidly and surgery is usually needed. An approach to detect PSC opacities in retro-illumination images is proposed. Watershed and Markov random fields (MRF) method are employed to opacities in anterior retro-illumination images. It results in a mixture of PSC, cortical opacities and noise. Then, information in both anterior and posterior retro-illumination images is utilized. Two features are extracted to identify PSC: mean gradient comparison (MGC) between anterior and posterior retro-illumination images, and spatial location. This is the first time that comparison between anterior and posterior retro-illumination images is proposed and MGC is proposed as the feature of comparison in PSC detection. Experiments show that the sensitivity and specificity of PSC screening is 91.2 and 90.1 %, respectively, based on the 519 pairs of testing images. To the best of our knowledge, it is the best performance reported in automatic detection of PSC. Compared with the methods in the literatures, considerable improvement is achieved when there are large areas of PSC opacities.

Indexed as

CataractEyeHumansSensitivity and SpecificityMarkov random fieldsMean gradient comparisonPosterior subcapsular cataractWatershed

Identifiers

PMID27491802
OpenAlexW2504300638

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.