PyJAMAS: open-source, multimodal segmentation and analysis of microscopy images

10Citations
Citations of this article
36Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Summary: Our increasing ability to resolve fine details using light microscopy is matched by an increasing need to quantify images in order to detect and measure phenotypes. Despite their central role in cell biology, many image analysis tools require a financial investment, are released as proprietary software, or are implemented in languages not friendly for beginners, and thus are used as black boxes. To overcome these limitations, we have developed PyJAMAS, an open-source tool for image processing and analysis written in Python. PyJAMAS provides a variety of segmentation tools, including watershed and machine learning-based methods; takes advantage of Jupyter notebooks for the display and reproducibility of data analyses; and can be used through a cross-platform graphical user interface or as part of Python scripts via a comprehensive application programming interface.

Cite

CITATION STYLE

APA

Fernandez-Gonzalez, R., Balaghi, N., Wang, K., Hawkins, R., Rothenberg, K., Mcfaul, C., … Castle, V. (2022). PyJAMAS: open-source, multimodal segmentation and analysis of microscopy images. Bioinformatics, 38(2), 594–596. https://doi.org/10.1093/bioinformatics/btab589

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free