CellProfiler 3.0: Next-generation image processing for biology

Claire McQuin, Allen Goodman, Vasiliy Chernyshev, Lee Kamentsky, Beth A. Cimini, Kyle W. Karhohs, Minh Doan, Liya Ding, Susanne M. Rafelski, Derek Thirstrup, Winfried Wiegraebe, Shantanu Singh, Tim Becker, Juan C. Caicedo, Anne E. Carpenter

    Research output: Contribution to journalArticlepeer-review

    724 Citations (Scopus)

    Abstract

    CellProfiler has enabled the scientific research community to create flexible, modular image analysis pipelines since its release in 2005. Here, we describe CellProfiler 3.0, a new version of the software supporting both whole-volume and plane-wise analysis of three-dimensional (3D) image stacks, increasingly common in biomedical research. CellProfiler’s infrastructure is greatly improved, and we provide a protocol for cloud-based, large-scale image processing. New plugins enable running pretrained deep learning models on images. Designed by and for biologists, CellProfiler equips researchers with powerful computational tools via a well-documented user interface, empowering biologists in all fields to create quantitative, reproducible image analysis workflows.

    Original languageEnglish
    Article numbere2005970
    JournalPLoS Biology
    Volume16
    Issue number7
    DOIs
    Publication statusPublished - 3 Jul 2018

    Fingerprint

    Dive into the research topics of 'CellProfiler 3.0: Next-generation image processing for biology'. Together they form a unique fingerprint.

    Cite this