Evidence map›Paper›PMID 31065419›Full record

ArticleBiomedical optics express2018

High-throughput label-free flow cytometry based on matched-filter compressive imaging.

Cong Ba, William J Shain, Thomas G Bifano, Jerome Mertz

Abstract read
In one paragraph

Article in Biomedical optics express, 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

4 authors.

Cong BaBiomedical Engineering Department, Boston University, 44 Cummington Mall, Boston, MA 02215, USA.
William J ShainPhotonics Center, Boston University, 8 Saint Mary's Street, Boston, MA 02215, USA.
Thomas G BifanoPhotonics Center, Boston University, 8 Saint Mary's Street, Boston, MA 02215, USA.
Jerome MertzBiomedical Engineering Department, Boston University, 44 Cummington Mall, Boston, MA 02215, USA.

Funding

Development of label-free computational flow cytometry for high-throughput micro-organism classificationR21GM128020 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI MERTZ, JEROME · 2018 to 2019
$446k
NIGMS NIH HHS R21 GM128020
6 · The paper itself

Abstract

We present a fast label-free computational flow cytometer based on a strategy of compressive imaging. Scattered light from flowing objects is sub-divided into user-defined basis patterns by a deformable mirror and routed to different detectors associated with each pattern. The patterns can be optimized to be matched to the object features of interest, thus facilitating object identification and separation. Compared to conventional scanning flow cytometers, our technique provides increased information capacity without sacrificing flow velocity. Unique features of our matched-filter strategy are that it can simultaneously probe multiple objects throughout large fields of view with long depths of field. In our proof-of-concept demonstrations, we achieve throughputs of over 10,000 particles/s, working at flow velocities of over 1m/s.

Identifiers

PMID31065419
PMCPMC6491006

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.