Imaging Data Provenance and 

Reproducibility

Tissue Microenvironment Group

Cardiff University, School of Medicine

Dimitris Parthimos

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Typical analysis pipeline
Image analysis - Pipeline in Action (CellProfiler)

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design/meta 

data

new cell paints

reference 

material/data

patient cells

Data collected at NIST: Static data

image analysis 

algorithms

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Original data 

190 GB

Reference data 

3.5 GB

Multiple 

experimental 

data

Data collected at NIST: Testing stability of data

In silico

generated data

569 GB

Other channels 

x3

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Case Study 2

Timelapse microscopy of live cells responding to drug

R.A. Howard-Jones, Marie Wiltshire, A.J. Sloan and R.J. Errington

Cardiff University, School of Medicine,

M.R. Brown and Matthieu Duteil

Swansea University, School of Engineering

J Elliott and Michael Halter

Cellular Biosystems, NIST

Peter Bajcsy and team

Information technology, NIST

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Collected on a high-throughput screening instrument designed to automatically 

collect an image sequence as a movie

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Typical video time lapse of cancer cell line

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• Derive behavioural features of cells in control and perturbed conditions

• Obtain features of clonal expansion and understand this expansion at different 

granularities, including lineages

• In cancer cells: understand the derivation (dynamics) of the polyploidy phenotype, 

and measure the neighbourhood in which these cells survive.

• Patterns of drug resistance, temporal and spatial characteristics of which are poorly 

understood

What do we want to extract from such timelapse image data

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Automated cell detection and tracking 

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Tiled 3x3 FOV

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Collected on a high-throughput screening instrument designed to automatically 

collect an image sequence a movie

For this one experiment: 108 FOV collected every 30 minutes for 120.5 hours: 2 channels

Each FOV = 1392*1040 therefore entire dataset is 72 Gigabytes

2 datasets one for cancer cell line and one for primary mesenchymal stem cells – 144GB

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Case Study 3

Extracellular vesicle activity associated with cancer resistance

Aled Clayton, Jason Webber

Cardiff University, School of Medicine,

Diamond

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...

Fluorescent microscope overlaid with x-ray beam

- Cryo Soft X-ray Τomograph

- Cryo Structured Illumination Microscope
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Fluorescent microscopy overlaid with x-ray beam image

+60o at 0.2o equivalent to 1.2 GB data size (x 100 cells x treatments)
Identify sources of variability in assay

Cause and effect diagram 16
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Image 

Data

Bio

Sample

Stem Cell 

Extraction

Instrumen

t Settings

Flow 

Data

Geneti

c Data

Cellular 

Databas

e

Data 

Analysis

Visual 

Analysis

Machine 

Learning/

Mathematic

al modelling

Single Cell 

Data 

Model

Experiment

al Design

Param Param Param Param

WET LAB DRY LAB

Image 

Analysis

Flow 

Analysis

Genetic 

Analysis

Cell

Quality

Artificial Intelligence

NIST- PABL

Data 

Acquisiti

on

Data 

Qualit

y

Param
Summary

• Bioimaging community faces an explosive growth in data size and 

complexity

• Reproducibility is a key concern; traceability of algorithm pipelines

• Fundamental need for tools such as Web Image Processing Pipeline (WIPP) 

and Automated Bio-Imaging Laboratories (NIST)

• Interactive measurements and AI-assisted discoveries over large image 

banks

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