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

Authors :
Moser LM
Gogoberidze N
Papaleo A
Lucas A
Dao D
Friedrich CA
Paavolainen L
Molnar C
Stirling DR
Hung J
Wang R
Tromans-Coia C
Li B
Evans EL 3rd
Eliceiri KW
Horvath P
Carpenter AE
Cimini BA
Source :
BioRxiv : the preprint server for biology [bioRxiv] 2024 Jun 04. Date of Electronic Publication: 2024 Jun 04.
Publication Year :
2024

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.

Details

Language :
English
Database :
MEDLINE
Journal :
BioRxiv : the preprint server for biology
Publication Type :
Academic Journal
Accession number :
38895349
Full Text :
https://doi.org/10.1101/2024.06.03.597232