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About

QuantiMus is a machine-learning based program used for histological analysis of skeletal muscle. Developed as a plugin for the image analysis tool flika, QuantiMus is a versatile, fast, and precise to complete histological analysis. QuantiMus is written in Python and is open-source.


Features

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Cross-sectional Area

Using machine-learning algorithms and novel segmentation techniques, QuantiMus is able to identify muscle fibers and determine their cross-sectional areas and minimum feret diameters.

Mobirise

Mean Fluorescence Intensity

QuantiMus allows the user to identify the mean fluorescence intensity in each individual fiber of a muscle section. This feature can be used in conjuction with any fluorescent stain that the user chooses.

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Centrally Nucleated Fibers

After identifying muscle fibers in a cross-section, QuantiMus is able to determine which muscle fibers are centrally nucleated.

Address

Villalta Laboratory
Physiology and Biophysics
3014 Hewitt Hall
University of California, Irvine
Irvine, CA 92697-4120

Contacts

Jenna Kastenschmidt,
PhD Candidate
jkastenschmidt@gmail.com

Kyle Ellesfen, PhD
kyleellefsen@gmail.com

Ali Mannaa
ali.h.mannaa@gmail.com

Website

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