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Analuse Globalisée des Données d ’Imagerie Radiologique
From Image Registration in Oncologyto Complex Workflows on the GRID
Xavier Pennec, PhD, INRIA-Sophia, projet EpidaureJohan Montagnat, PhD, I3S, Rainbow team, Tristan Glatard, I3S, Rainbow + INRIA, Epidaure teamsPierre-Yves Bondiau, MD, PhD, Centre Antoine Lacassagne, Nice
AGIR - Sophia 2
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Overview
• The Medical application: – Registration for oncology
• The scientific question:– Evaluation / comparison of registration algorithm performances
• The technical challenge:– Running the workflow on the GRID
AGIR - Sophia 3
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Image Registration for Oncology
• Registration / segmentation are basic components of medical image analysis– Registration: finding homologous points / tranformation– Segmentation: give anatomical label to each image point
• Registration for brain radiotherapy– Planning
Fusion of image modalities (multimodal, rigid) Warp atlas to patient image for segmentation
(mono-modal, non-rigid) Definition of Target volumes and Organs at risk: dose optimization
– Follow-up (monomodal rigid)
http://www.healthgrid.org/docs/pdf/WhitePaperdraft_v1.1-3reviewedv2.pdf (ch 3/4)
AGIR - Sophia 4
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Inter-subject registrationAffine transformation
Correct size and position but high remaining variability in cortex and deep structures
MR T1 Images
256x256x120 voxels
Atlas to patient registrationfor radiotherapy planning
Image Registration for Oncology
AGIR - Sophia 5
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Anatomically meaningful deformationRegistration in 5 min on 15 PCs
Adaptive non-stationary visco-elastic inter-subject registration
Image Registration for Oncology
AGIR - Sophia 6
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Atlas
Propagate the segmentation of structure of interest from the atlas to the patient image
AGIR - Sophia 7
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Image Registration for Oncology
• Define target volume and organs at risk thanks to the segmentation• Optimize the irradiation process to
– maximize the dose within the tumor – minimize it within neighboring organs at risk
AGIR - Sophia 8
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Image Registration for Oncology
• There is no universal registration algorithm– More than 600 references on medical image registration in 1997– More than 100 papers each year… (70 at MICCAI 2004 only)
• Registration algorithms as Grid services
– Use up to date algorithm– Evaluation / comparison of algorithm performances
• Challenges– Inter-operability (coordinate systems, transformation format…)– Ontology describing data, registration problems and algorithms
AGIR - Sophia 9
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Overview
• The Medical application: – Registration for oncology
• The scientific question:– Evaluation / comparison of registration algorithm performances
• The technical challenge:– Running the workflow on the GRID
AGIR - Sophia 10
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Variability of a registration algorithm
Registration algorithm
Final transformation
External parameters
• Data (image) 1
• Data (image) 2
• Acquisition noise
• Patient effects
Varying internal parameters
• Initial transformation
• (…)
• Robustness: ability to find the right transformation (success/failure)
• Precision: Repeatability w.r.t. some parameters (e.g. initialization)
• Accuracy: Variability w.r.t. the ground truth for typical data
Fixed internal parameters
• Multiscale resolution
• (Typical variance…)
AGIR - Sophia 12
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
• Uncertainty = deviation from the real transformation– Maximum error: bound– Mean Error: covariance matrix, std dev.
On the transformation ( rotation r [rad], translation t [mm])
On test points (TRE x)
Quantifying the registration errors
• Robustness: – size of the basin of attraction– Probability of convergence
AGIR - Sophia 16
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Performance evaluation and validation
• Synthetic data (simulation): – Available ground truth– Difficult to identify and model all sources of variability
• Real data in a controlled environment (Phantom):– Possible gold standard– Performances evaluation in specific conditions
Difficult to test all clinical conditions May hide a bias
• Image database representative of the clinical application– Usually no ground truth– Should span all sources of variability
AGIR - Sophia 18
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
• Bronze standard: The exact result is an unknown
variable– Unbiased estimation: use redundant information
use many different registration algorithms(average biases, so that precision ~ accuracy)
Use many different data (redundant information to ensure precision) Average transformations (maximal consistency)
• Data intensive application:– High number of images across different databases– High number of registration algorithms
Performance Evaluation without Gold Std
AGIR - Sophia 19
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Multiple a posteriori registration
• Best explanation of the observations (ML) :– Robust Fréchet mean– Robust initialisation and Newton gradient descent
• Result
2221
2 ),,(min),( TTTTd i
transrotjiT ,,,
AGIR - Sophia 20
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Example bronze std
222/
2 2 USMRUSMRloop
AGIR - Sophia 21
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
• Data intensive application:– High number of images across different databases– High number of registration algorithms
• Grid validation protocol (PhD Tristan Glatard)– Find available data that match the problem description– Find the algorithms that can deal with them– Find and organize the resources to do the job
Performance Evaluation without Gold Std
AGIR - Sophia 22
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Bronze Std workflow
CrestMatch
PFMatchICP
PFRegisterYasmina
Baladin
Resultsmanagement
Format conversion
Crest lines extraction
Format conversion
Results management
Formatconversion
Results management
Format conversion
Results management
Target image :- Image1- Image2- ...
Registrationalgorithms
Othercomponents
data links
input
output
Floating image :- Image1- Image2- ...
The bronze standard workflow
AGIR - Sophia 23
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Overview
• The Medical application: – Registration for oncology
• The scientific question:– Evaluation / comparison of registration algorithm performances
• The technical challenge:– Running the workflow on the GRID
AGIR - Sophia 24
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Workflow manager
• Workflow description – components / links– Taverna is the most powerful
• Workflow Execution – Use the available parallelism (different notions of grid….)– Taverna has severe limitations
• Control issues
AGIR - Sophia 25
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Workflow description
• Description of processing components (web services)– Interface (e.g. WSDL), independent of their implementation– Example:
<message name="registrateWithCrestMatchRequest">
<part name="reference" type="xsd:string"/>
<part name="floating" type="xsd:string"/>
<part name="crest-ref" type="xsd:string"/>
<part name="crest-float" type="xsd:string"/>
<part name="input-comment" type="xsd:string"/>
</message>
<message name="response">
<part name="result-image" type="xsd:string"/>
<part name="result-voxel-transfo" type="xsd:string"/>
<part name="result-real-transfo" type="xsd:string"/>
<part name="reference-image" type="xsd:string"/>
<part name="floating-image" type="xsd:string"/>
<part name="comment" type="xsd:string"/>
</message>
<SOAP:address location="http://colors.unice.fr:18002"/>
AGIR - Sophia 26
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Workflow description
• Description of processing components (web services)– Interface (e.g. WSDL), independent of their implementation– Description is syntactic, not semantic
• Description of links between components
– Control links (from e-business): BPEL4WS – WSCDL
– Data links (from e-science) Scufl (Taverna)Scufl (Taverna) – MoML (Kepler)
<sequence><flow><switch><while><wait>BPEL tags
<processor><source><sink><link>
Scufl tags
AGIR - Sophia 27
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Taverna
• Chosen workflow management tool: Taverna – Developed in the UK project myGrid (bioinformatique)– Open source : http://taverna.sourceforge.net– Based on web-services– Most powerful workflow manager for description
• Current research (e.g. in myGrid, UK)– Semantic annotation of services through ontologies– Automatic transcription into translating units
Limitation of translating units needed for algorithm compatibility Systematic discovery of available components
AGIR - Sophia 28
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Taverna
• Limitations of the data iteration strategy description– Scufl:
dot and cross products operators
– In our case: register all images of the same patient
the same modality
A different exam date
Set 0 Set 1
I0
J0
I1
J1
I2
J2
Ref Img Flo Img
A0
A0
A1
A1
A2
A2
B0
B0
B1
B1
Set 0 Set 1
I0
J0
I1
J1
I2
J2
AGIR - Sophia 29
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Taverna: Execution
• Interaction of Taverna with the grid (EGEE)
• Exloiting the parallelism of the workflow– Splits and synchronize, e.g.
C1: Initialization C2: Register Algo 1 C3: Register Algo 2 C4: avarage results
– Taverna is OK for one data…
Tavernaworkflowmanager
RegistrationWeb-Service
EGEE User InterfaceSOAP
(over HTTP)ssh
tunnellingcommand line
interface
Grid Resources
C1
C2
C3
C4
D0
AGIR - Sophia 30
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Exploiting parallelism
• Data parallelism: – components are not multithread in Taverna!– Patch with submission/fetching services
Data order is not preserved (send 1/2/3, receive 3/1/2) Need a track record for each result
C1
C2
C3
C4D
0, D
1, D
2
–Asynchronous interactionTaverna Submission
service
Fetchingservice
GridMonitor2Monitor1
query1
query2
Taverna Web-Service Grid
computation1
query1
result1
computation2
query2
result2
result2
result1
com
pu
tati
on1
com
pu
tati
on2
– Synchronous interaction
AGIR - Sophia 31
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Exploiting parallelism
• Data + component parallelism: streaming (Pipelining)
Nw sequential steps, ND Data sets, Mean time T per component
Execution time = ND.Nw.T vs (ND+Nw-1).T
– Example for registration:
nD = 50 ; n
W = 4 ; T = 30min
Execution time = 100h vs 26.5 h
• Streaming is not possible with Taverna
C1
C2
C3
C4D
0, D
1, D
2
C1 D0 D1 D2 - - - -
C2 - - - C1*D0 C1*D1 C1*D2 -
C3 - - - C1*D0 C1*D1 C1*D2 -
C4 - - - - - - Mean
C1 D0 D1 D2 - -
C2 - C1*D0 C1*D1 C1*D2 -
C3 - C1*D0 C1*D1 C1*D2 -
C4 - - - - Mean
AGIR - Sophia 32
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
A new workflow execution engine
• Development of a new execution engine
– compatible with Taverna description (Scufl)
– Allowing data and Component parallelism
– Implementing result traceability
– Article submitted, soft to be available at
http://www.i3s.unice.fr/~glatard
AGIR - Sophia 33
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Controlling the execution
• Taverna and the new execution engine handle:– The traceability of results (execution tree for each data)
• Taverna handles:– Re-submissions and delays– Alternative but predefined locations of web-services
• Remaining issues– Nor Taverna nor EGEE handles
Job submission errors Cancelled or lost jobs Timeouts
– How to do that without stopping the workflow execution?– Is it a middleware or a workflow manager issue?
AGIR - Sophia 34
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Conclusion - perspectives
• Prototype of a new execution engine for Taverna – Exploiting streaming parallelism– Control of traceability
• Open questions– Including ontologies– Granularity of jobs on the grid– Reliable interface with the EGEE infrastructure
(timeouts/errors)
• The Bronze standard application– Verification phase (standardization / converters)– Coupling with ontologies– Benchmark for
registration algorithms Compression Workflow execution engines on the grid
AGIR - Sophia 35
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
References
• Bronze Standard Granger et al, MICCAI 2001 & ECCV 2002. Nicolau et al, IS4TM 2003.
• Worflows on GRIDS T. Glatard & al. Grid-enabled workflows for data intensive
applications. IEEE Int. Symp. On Computer-based Medical Systems CBMS’05.
T. Glatard & al. An optimized workflow enactor for data-intensive grid applications, Submitted to IEEE/ACM Intern. Work. On Grid Computing 2005 (associated to Supercomputing 2005).
AGIR - Sophia 36
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
AGIR - Sophia 37
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
• Scenario 1: user accesses to registration services through the grid on his own data
• Scenario 2: the user test his algorithm on standard image databases
User
GRIDRegistration
service
Computer resources
Image dataresources
Grid registration services
AGIR - Sophia 38
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Interoperability challenges
• Image format (input / output) Dicom (communication module ?) Basic 3D image format ?
• Transformation formats Standardized displacement field / resampled image Internal representation + std resampling function
• Algorithm parameters / options Define std param. w.r.t. classes of registration problems
• Interactivity State of advancement (reporting) Interactive corrections
Grid registration services
AGIR - Sophia 39
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Ontology of Algorithms (registration service)
• Type of data Images (2D, 3D, time series) Point clouds, landmarks
• Type of spatial transformation Rigid / similarity / affine Non rigid (global / local) (splines, def. Fields, polyrigids…)
• From Data to Transformation Comparison metric (SSD, Correlation coefficient)
takes into account the intensity transformation Optimization procedure Interactivity
Grid registration services
AGIR - Sophia 40
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Ontology of Registration Problems (image databases)
• Modality involved (specifies the type of data) Monomodal (CT, MR, US, Video, point measures…) Multimodal (combination of above) Atlas to modality
• Image content (specifies the type of transformation) Anatomical part concerned (head, thorax, abdomen…) Changes expected
• intrasubject / intersubject / atlas• Smooth evolution / pathology
Grid registration services
AGIR - Sophia 48
Analyse Globalisée des Données d’Imagerie Radiologique
www.aci-agir.org
Interactive volume
reconstuctionA. Osorio
Workflow Management J. Montagnat
MedicalApps.
Les thématiques
Cardiological images
SegmentationI. Magnin
Humanitarian Medical
DevelopmentV. Breton
Image registration in oncologyX. Pennec
Dissem
ination C. G
ermain
Services for InteractivityC. Germain
Middleware evaluation E. Jeannot
Medical data ManagementJ. Montagnat
Medical data access
protocols J-M. Moureaux
CoreGrid
MedicalServices
AlgorithmGridification
Medical applications evaluation P-Y Bondiau