Image-Based Steering for Integrative Biology

Lakshmi Sastry, Richard Wong, Helen Wrightwith contributions from Ronald Fowler, Sri Nagella and Anjan Pakhira

Acknowledgements

Ken Brodlie and Jason Wood CompuSteer funding Integrative Biology project scientists

Image-based Steering

SimulateFilterMapRender

Visualization processingIntegrated display

X

X

Integrative Biology (IB)

Grid technology to enable in-silico experiments by computational biologists

Combined resources for computation, data management, visualization and data analysis

Focus on fatal diseases – heart and cancer

Example IB Applications

Modelling heart electrical activity during arrhythmia:

Tulane whole ventricular model – epicardial potential distribution over heart geometry during shock-induced arrhythmia

Fenton-Karma 4-variable model on 2D slice of tissue

An episode of arrhythmogenesis in ventricular model. The arrhythmia is a figure of eight reentry with one rotor on the anterior (left panel) and another on the posterior (right panel) of the ventricles. The arrows show wave propagation. The scale is saturated, potentials above 20mV are shown in red and below -90mV are shown in blue.

Example IB Applications

In vitro and in-silico models of tumour growth during very early stages

Seamless secure access to very large volumes of image data, processing, simulation and interaction will accelerate understanding of disease process.

Steering for IB Applications Complex and compute intensive with

tens and hundreds of parameters Verification of models that continue to

be refined Computational exploration of

parameter space Expanding set of simulations and

visualization toolkits

Image-based Interaction Extrinsic parameters (scalars,

vectors) mimic widgets but minimise context switching

Parameters intrinsic to the solution graphic, e.g. position specifications

The IB interface provides a layer of abstraction above the clientside libraries for computational steering.

The Case for Server-side Applications

Application may already have steering embedded

Developing a steerable interface and other scalable services for each application does not scale

Difficult to embed steering and other services into certain visualization toolkits

Users want continuity in their visualization toolkits

Minimises changes needed to application software

Client-side Consequences

Keep client generic – configure on set-up to meet application requirements

Needs to handle various geometry and image formats

Application-specific activity e.g. to resolve geometry elements or nodes, takes place server-side

IB Interface

Visualisation & interactors

panel

Control panel of widgets gViz

clientside

IB Interface

Visualisation & interactors

panel

Control panel of widgets gViz

clientside

Client A

Simulation (e.g. CARP)

gViz sim. module

Steer

View

Visualisation toolkit (e.g. Meshalyser)

IB Server

Data

Image & image based parameter values from coder/decoder

Steer

View

Client B

Collaborative gViz Overview Parameter changes are passed to all

collaborators for visibility (steer/view arrows)

Committed parameters are passed to all collaborators and the simulation, locking interactors

Arrival of data unlocks interactors – implies token-passing

Data streams – not used here – separate results from parameters

Demonstrator Elements Tumour modelling – growth of ductal

carcinoma in breast Results – time-varying tumour cell

counts in axial and radial direction of duct

Steering of nutrient consumption rate and cell-to-duct-wall slip coefficient

Utilises gViz rel.2 (collaborative) for parameter passing, calling Fortran

Visualization Back-end

IRIS Explorer, loosely coupled Simulation outputs file of results (time

step) which triggers visualization Height-field plot varying in time

height = cell numbers colour = pressure

Steering nutrient consumption and cell death rate (6MB movie)

OpenGL Interactors

Experiences

Hard to ‘wipe the slate clean’ before starting again

New collaboration helps Mode is ‘extreme collaboration’ (cf.

extreme programming) Needs dedicated time Trips - how long is ‘just long enough’?

Remaining Question Marks

Token maintenance over the various architecture pathways

Recombination of 3rd party geometries/images with interactors Anticipate little problem for extrinsics Intrinsics more difficult

gViz and multiple simulations?

Remaining Question Marks

How scalable is the architecture really?

Will scientists and steering libraries ever really mix?

What support do scientists need to use steering libraries – documentation, examples, GUI builders?