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MORPHEUS: An automated tool for unbiased and reproducible cell morphometry
Author(s) -
Ruffinatti Federico Alessandro,
Genova Tullio,
Mussano Federico,
Munaron Luca
Publication year - 2020
Publication title -
journal of cellular physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.529
H-Index - 174
eISSN - 1097-4652
pISSN - 0021-9541
DOI - 10.1002/jcp.29768
Subject(s) - computer science , reproducibility , artificial intelligence , orientation (vector space) , set (abstract data type) , nonparametric statistics , fluorescence microscope , microscopy , pattern recognition (psychology) , computer vision , fluorescence , chemistry , mathematics , statistics , chromatography , pathology , physics , medicine , geometry , quantum mechanics , programming language
Abstract Here we present a new Fiji/ImageJ2 plugin called Multiparametric Morphometric Analysis of EUcaryotic cellS (MORPHEUS), designed for the automated evaluation of cell morphometry from images acquired by fluorescence microscopy. MORPHEUS works with sampling distributions to learn—in an unsupervised manner and by a nonparametric approach—how to recognize the cells suitable for subsequent analysis. Afterward, the algorithm performs the evaluation of the most relevant cell‐shape descriptors over the full set of detected cells. Optionally, also the extraction of nucleus features and a double‐scale analysis of orientation can be performed. The whole algorithm is implemented as a one‐click procedure, thus minimizing the user's intervention. By reducing biases and errors of human origin, MORPHEUS is intended to be a useful tool to enhance reproducibility in the bioimage analysis.
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