This document discusses quantitative image analysis techniques for extracting information from 2D, 3D, time-lapse, and spectral biological images captured with microscopes. Traditional manual analysis is time-consuming and prone to bias, while high-throughput experiments generate millions of images. Quantitative image analysis software is used to automatically measure rates of cell division, protein localization, responses to drugs, lineage tracing, motility, and more from images of samples like yeast strains, tissue cultures, and tumor biopsies to aid in applications such as disease detection, survival prediction, and embryogenesis tracing.

1. Quantitative Image Analysis
in the Life Sciences
Simon Li
someone@pitpe.co.uk
1

2. Introduction
The use of image and data
analysis techniques to extract
quantitative information from 2D, 3D, Time-lapse, Spectral
images of biological samples. imaging
Light microscopy, Confocal, Multi-
photon, Electron microscopy, ...

3. Introduction
The use of image and data
analysis techniques to extract
quantitative information from 2D, 3D, Time-lapse, Spectral
images of biological samples. imaging
Light microscopy, Confocal, Multi-
photon, Electron microscopy, ...
Why?
Traditional analysis of microscope Humans are prone to bias, and get
images is a time-consuming bored easily.
manual process
Biologists and clinicians have
High throughput (robot assisted) superior expert knowledge, and are
experiments may generate millions able to make inferences from very
of images little information

4. Some applications
Cell biology Software:
Rates of cell division Opensource:
Spatio-temporal protein localisation ImageJ, CellProfiler
Responses of cells to new drugs R, Python, ITK, VTK
Lineage tracing
Cell motility Proprietary:
Matlab, MetaMorph, Volocity, ...
Disease detection and diagnosis
Analysis of tumour biopsies
Retinal blood vessel tracing
Cell counting
Analysis of fungal networks
3D reconstruction
Tracing embryo development

5. Yeast strains (5000+)

8. Mitosis / cell division
Highly choreographed process in which DNA is
duplicated and a cell divides into two new cells
Problems can lead to cancer

10. Tissue culture

12. Tumour biopsies

13. Survival prediction
100 patients
Machine Learning:
Random forests
Potentially predictive
features identified

14. Simon Li
someone@pitpe.co.uk