dr yinhai wang david mccleary, ching-wei wang, jackie james, dean fennell, peter hamilton
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Dr Yinhai Wang David McCleary, Ching-Wei Wang, Jackie James, Dean Fennell, Peter Hamilton. Introduction. Tissue Microarrays. Key technique for high throughput single assay platform for tissue biomarker research and discovery. - PowerPoint PPT PresentationTRANSCRIPT
High Performance Computing for Tissue MicroArray Analysis
Dr Yinhai WangDavid McCleary, Ching-Wei Wang, Jackie
James, Dean Fennell, Peter Hamilton
Introduction
Tissue Microarrays
Key technique for high throughput single assay platform for tissue biomarker research and discovery.
*Dolled-Filhart and Rimm, Principles and Practice of Oncology, 7th Edition, Chapter 7, 2004.
232 Tissue Cores
The Bottleneck
Relies on visual scoring of tissue biomarkers by pathologists. It is time consuming, subjective and prone to error.
103,790×58,586 pixels17GB
Image Analysis of TMA Virtual Slides
A TMA virtual slide is an ultra-large digital image, scanned at a high magnification (40X).
Computer assisted analysis using TMA virtual slides.Objective and reproducible.Speed?
Objective
Objective
Automate TMA analysisGenuine high throughput
platformReduce pathologists workloadSpeedup biomarker discovery
Materials and Methods
Hewlett-Packard Blade Server. Intel Xeon quad-core x86_64
processors.>9,000 processor-cores
available. 10-16GB memory per node (8
cores).Gigabit Ethernet connection.Fibre connection to hard disks
(SAN).
High Performance Computing (HPC) Platform
Parallel Processing Module
Glass slide
Image generation
Digital SlideServing Module
Image File Access Module
Analytical Module
TMA Database
Viewing
Instructions
Results
High resolution image
HPC Platform Visualisation
High Performance Computing
Colour conversi
on
Vendor format independentBGR BGRRegion
extraction Raw image
JPEG decoder
Compressed?uncompressed data
RGB GB
Pixel (n,0) Pixel (0,1)
Hamamatsuvirtual slide
No
Yes
Regionextraction Raw image
JPEG decoder
Compressed?Aperio
virtual slideNo
Yes
uncompressed dataB GR G R
Pixel (0,0) Pixel (0,1)
a
Format?
JPEG 2000decoder
JPEG 2000
JPEG
Regionextraction Raw image
JPEG decoder
Compressed?Carl Zeiss
virtual slideNo
Yes
uncompressed dataRGB RG
Pixel (0,0) Pixel (0,1)
B Colour conversi
on
Colour conversi
on
HPC: Image File Access Module
Master Worker 1 Worker 2 Worker 3 Worker 4Database
A1 B1 C1 D1
A2 B2 C2 D2
Request for corecoordinates
TMA core location (x, y) at TMA virtual slide
Assign toavailable workers
1
2 3Storage
Locate Image in Storage and Core Sub-image
4
Retrieve and LoadCore Sub-image
5
Analyse and return results
6
7Analyse and
return results
6
Informs Master itis now available
Centralised Dynamic Load Balancing
HPC: Parallel Processing Module
HPC: Analytic Module
Texture feature calculation◦ Tumour pattern recognition◦ Tumour region identification
HPC: Analytic Module
Automated quantisation of biomarker IHC density on TMA core images, using colour decomposition.
www.pathxl.com
HPC: Digital Slide Serving Module
Results
•106,290×65,017 pixels•19.3GB•229 Tissue Cores Speedup=(Fastest Sequential Code)/(Parallel
Code)=42.58
Texture Pattern Calculation for TMA Slides
Time for Loading vs. Saving
Time for actual Texture Feature Calculation
Loading, Storing, Texture
Processing time: 30minutes77secondsSpeedup=22.19
Biomarker Quantification
Multi TMA Slides
There are >9000 processor-cores available
The processing of 1 TMA virtual slide uses <100 processor-cores.
>90 TMA virtual slides can be processed simultaneously (≈1 minute).
Genuine high throughput platform for multiplex multi-TMA studies.
Conclusion• A novel high performance computing
platform for the rapid analysis of TMA virtual slides.
• The centralised load balancing approach is proven to be robust.
• It significantly speedups up the analysis of TMAs, removing the bottleneck.
• Valuable platform for TMA research & biomarker discovery.
• High performance platform for the algorithm prototyping, development & evaluation.
Acknowledgements