Evidence map›Paper›PMID 38895349›Full record

ArticlebioRxiv : the preprint server for biology2024

Piximi - An Images to Discovery web tool for bioimages and beyond.

Levin M Moser, Nodar Gogoberidze, Andréa Papaleo, Alice Lucas, David Dao, Christoph A Friedrich, Lassi Paavolainen, Csaba Molnar, David R Stirling, Jane Hung and 8 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

18 authors.

Levin M MoserImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.ORCID 0000-0002-4212-404X
Nodar GogoberidzeImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.ORCID 0000-0002-9395-4676
Andréa PapaleoImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.ORCID 0000-0003-2269-9337
Alice LucasImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.ORCID 0000-0001-5914-4154
David DaoETH Zurich, Zurich, Switzerland.
Christoph A FriedrichImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.
Lassi PaavolainenInstitute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.ORCID 0000-0003-1508-2718
Csaba MolnarImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.ORCID 0000-0002-6124-1209
David R StirlingImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.ORCID 0000-0001-6802-4103
Jane HungDepartment of Chemical Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
Rex WangData Sciences Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.
Callum Tromans-CoiaImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.ORCID 0000-0002-5518-8915
Bin LiCenter for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0003-0695-393X
Edward L EvansCenter for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0003-0278-4227
Kevin W EliceiriCenter for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0001-8678-670X
Peter HorvathSynthetic and Systems Biology Unit, HUN-REN Biological Research Centre (BRC), Szeged, Hungary.ORCID 0000-0002-4492-1798
Anne E CarpenterImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.ORCID 0000-0003-1555-8261
Beth A CiminiImaging Platform, Broad Institute of MIT and Harvard, Cambridge MA, USA.ORCID 0000-0001-9640-9318

Funding

Center for Open Bioimage AnalysisP41GM135019 · NIGMS · BROAD INSTITUTE, INC. · PI CARPENTER, ANNE E., CIMINI, BETH · 2020 to 2024
$6.9M
Extracting rich information from biological imagesR35GM122547 · NIGMS · BROAD INSTITUTE, INC. · PI Anne E. Carpenter · 2017 to 2026
$6.2M
NIGMS NIH HHS P41 GM135019NIGMS NIH HHS R35 GM122547
6 · The paper itself

Abstract

Deep learning has greatly accelerated research in biological image analysis yet it often requires programming skills and specialized tool installation. Here we present Piximi, a modern, no-programming image analysis tool leveraging deep learning. Implemented as a web application at Piximi.app, Piximi requires no installation and can be accessed by any modern web browser. Its client-only architecture preserves the security of researcher data by running all computation locally. Piximi offers four core modules: a deep learning classifier, an image annotator, measurement modules, and pre-trained deep learning segmentation modules. Piximi is interoperable with existing tools and workflows by supporting import and export of common data and model formats. The intuitive researcher interface and easy access to Piximi allows biological researchers to obtain insights into images within just a few minutes. Piximi aims to bring deep learning-powered image analysis to a broader community by eliminating barriers to entry.

Identifiers

PMID38895349
PMCPMC11185650

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.