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Mahotas specifications

Information


Unique identifier OMICS_27359
Name Mahotas
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages C++, Python
License MIT License
Computer skills Advanced
Version 1.4.4
Stability Stable
Maintained Yes

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Additional information


http://mahotas.readthedocs.io/en/latest/install.html

Publication for Mahotas

Mahotas citations

 (12)
library_books

Accurate label free 3 part leukocyte recognition with single cell lens free imaging flow cytometry

2018
PMCID: 5933530
PMID: 29573668
DOI: 10.1016/j.compbiomed.2018.03.008

[…] between moments is maximally reduced. zernike moments have been favorably used as shape descriptors for cell images [, , ]. here, we calculated twenty-five zernike moments using the approach of mahotas [] with degree = 8., the feature extraction step produces feature vectors with a total of 60 elements per data sample. the resulting high dimensional feature space might cause many machine […]

library_books

UXT is required for spermatogenesis in mice

2018
PMCID: 5896988
PMID: 29649254
DOI: 10.1371/journal.pone.0195747

[…] fields from one tissue section at 20x magnification, counting between 400 and 2600 total nuclei per biological replicate. the following python packages were used for the analysis: opencv [], mahotas [], scikit-image [], and scikit learn []., testes were dissected by removing the tunica, snap-frozen in a dry ice-ethanol bath, and stored at -80°c until rna isolation. rna was isolated […]

library_books

Machine Learning for Nuclear Mechano Morphometric Biomarkers in Cancer Diagnosis

2017
PMCID: 5738417
PMID: 29263424
DOI: 10.1038/s41598-017-17858-1

[…] tensorflow and trained on an nvidia titan x pascal 12gb gpu. our logistic regression model was implemented in python using scikit-learn and feature extraction for the linear model was done using the mahotas python library. image segmentation on an nvidia titan x pascal 12gb gpu took roughly 0.5 seconds per 512 × 512 image containing several nuclei. as an example, training our cnn for classifying […]

library_books

Plakophilin 2 is required for transcription of genes that control calcium cycling and cardiac rhythm

2017
PMCID: 5524637
PMID: 28740174
DOI: 10.1038/s41467-017-00127-0

[…] in imagej. distances between clusters were obtained using the imagej function “analyze particles” and a script written in python that utilized the image processing packages “scikit-image” and “mahotas”., mice were anesthetized with carbon dioxide inhalation, perfused with 2% paraformaldehyde and 2.5% glutaraldehyde in pbs and then euthanized by excision of the heart. the perfused heart […]

library_books

Graphene–Metal Composite Sensors with Near Zero Temperature Coefficient of Resistance

2017
PMCID: 5331455
PMID: 28261691
DOI: 10.1021/acsomega.7b00044

[…] and electrically addressed with eutectic gallium–indium (egain)., an object-oriented python code was developed to perform image analysis of the sem images. this code made extensive use of the mahotas package (see supporting information) to distinguish the metal from graphene, identify separate nanoislands, and quantify the area of the individual nanoislands as well as their fractional […]

library_books

Quantitative 3D imaging for cell biology and ecology of environmental microbial eukaryotes

2017
PMCID: 5663481
PMID: 29087936
DOI: 10.7554/eLife.26066.043

[…] to detect the same object in multiple fields, thus we assign it to its canonical field based on the geometry and remove it from all other fields (see ). image analysis was performed using the mahotas package ()., each object is processed independently to extract sub-objects and features. sub-objects are identified using the same thresholding procedure as above (however, […]


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Mahotas institution(s)
Lane Center for Computational Biology, Carnegie Mellon University Instituto de Medicina Molecular
Mahotas funding source(s)
Supported by the Fundacao para a Ciencia e Tecnologia (grants SFRH/BD/37535/2007 and PTDC/SAU-GMG/115652/2008), by NIH grant GM078622, by a grant from the Scaife Foundation, by the HHMI Interfaces Initiative, and by a grant from the Siebel Scholars Foundation.

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