Evidence map›Paper›PMID 29376103›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2018

Virtual assessment of stereoscopic viewing of digital breast tomosynthesis projection images.

Gezheng Wen, Ho-Chang Chang, Jacob Reinhold, Joseph Y Lo, Mia K Markey

Abstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Gezheng WenUniversity of Texas at Austin, Electrical and Computer Engineering, Austin, Texas, United States.ORCID https://orcid.org/0000-0003-2993-9663
Ho-Chang ChangUniversity of Texas at Austin, Electrical and Computer Engineering, Austin, Texas, United States.ORCID https://orcid.org/0000-0002-0694-8359
Jacob ReinholdUniversity of Texas at Austin, Applied Research Laboratories, Austin, Texas, United States.ORCID https://orcid.org/0000-0001-8539-3103
Joseph Y LoDuke University School of Medicine, Diagnostic Radiology, Durham, North Carolina, United States.ORCID https://orcid.org/0000-0002-9540-5072
Mia K MarkeyUniversity of Texas at Austin, Biomedical Engineering, Austin, Texas, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital breast tomosynthesis (DBT) acquires a series of projection images from different angles as an x-ray source rotates around the breast. Such imaging geometry lends DBT naturally to stereoscopic viewing as two projection images with a reasonable separation angle can easily form a stereo pair. This simulation study assessed the efficacy of stereo viewing of DBT projection images. Three-dimensional computational breast phantoms with realistically shaped synthetic lesions were scanned by three simulated DBT systems. The projection images were combined into a sequence of stereo pairs and presented to a stereomatching-based model observer for deciding lesion presence. Signal-to-noise ratio was estimated, and the detection performance with stack viewing of reconstructed slices was the benchmark. We have shown that: (1) stereo viewing of projection images may underperform stack viewing of reconstructed slices for current DBT geometries; (2) DBT geometries may impact the efficacy of the two viewing modes differently: narrow-arc and wide-arc geometries may be better for stereo viewing and stack viewing, respectively; (3) the efficacy of stereo viewing may be more robust than stack viewing to reductions in dose. While in principle stereo viewing is potentially effective for visualizing DBT data, effective stereo viewing may require specifically optimized DBT image acquisition.

Indexed as

digital breast tomosynthesisdisparitymodel observerreconstructionstereo matchingstereoscopic viewing

Identifiers

PMID29376103
PMCPMC5771135

What OpenQuestion holds

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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.