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CellProfiler 3.0: Next-generation image processing for biology

Claire McQuin, Allen Goodman, Vasiliy S. Chernyshev, Lee Kamentsky, Beth A. Cimini, Kyle W. Karhohs, Minh Doan, Liya Ding, Susanne M. Rafelski, Derek Thirstrup,

PLoS Biology · 2018 · 2.1K citations · 31 references

DOI Full text

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TL;DR

CellProfiler, released in 2005, has enabled biologists to build flexible, modular image analysis pipelines through a well‑documented user interface, empowering quantitative, reproducible workflows across fields. The paper introduces CellProfiler 3.0, a new version that supports whole‑volume and plane‑wise analysis of 3D image stacks. CellProfiler 3.0 features an improved infrastructure, a protocol for cloud‑based large‑scale processing, and new plugins that allow running pretrained deep‑learning models on images.

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.