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2018_mcquin_PLOSBio

Repository for 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.

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 pre-trained 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.

All pipelines were initially designed to run in CellProfiler 3.0.0; all FIJI macros in FIJI-ImageJ1.51N with MorpholibJ 1.3.3.

The workflows herein correspond to the following Broad Bioimage Benchmark Collection entries

  • hiPSCs_Fig1 = BBBC034 (AICS-12_134)
  • hiPSCs_Fig4 = BBBC034 (colony_center and edge)
  • MouseBlastocyst_Fig2A_Fig3_S2Fig = BBBC032
  • MouseTrophoblast_Fig2B_S3Fig = BBBC033
  • SyntheticHL60_Fig2C_S4Fig = BBBC024 (v1_c00_lowSNR_images)
  • SyntheticHL60_TimeCourse_Fig2D_S5Fig = BBBC035

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