CellProfiler™: Free, Versatile Software for Automated Biological Image Analysis

TLDR

Visual analysis of biological samples is powerful yet repetitive, tedious, and subjective. The study describes using CellProfiler™ to automatically identify and measure diverse biological objects in images. CellProfiler™ automatically identifies, counts, and records detailed measurements of objects in digital images, enabling analysis from small datasets on a personal computer to large-scale studies on a computing cluster. The free, user‑friendly software allows biologists to quantitatively analyze diverse questions without custom programming, accelerating discovery across many fields.

Abstract

Careful visual examination of biological samples is quite powerful, but many visual analysis tasks done in the laboratory are repetitive, tedious, and subjective. Here we describe the use of the open-source software, CellProfiler™, to automatically identify and measure a variety of biological objects in images. The applications demonstrated here include yeast colony counting and classifying, cell microarray annotation, yeast patch assays, mouse tumor quantification, wound healing assays, and tissue topology measurement. The software automatically identifies objects in digital images, counts them, and records a full spectrum of measurements for each object, including location within the image, size, shape, color intensity, degree of correlation between colors, texture (smoothness), and number of neighbors. Small numbers of images can be processed automatically on a personal computer, and hundreds of thousands can be analyzed using a computing cluster. This free, easy-to-use software enables biologists to comprehensively and quantitatively address many questions that previously would have required custom programming, thereby facilitating discovery in a variety of biological fields of study.