CATI Pitié-Salpêtrière CATI: A national platform for advanced Neuroimaging In Alzheimer’s...

CATI Pitié-Salpêtrière

CATI: A national platform for advanced Neuroimaging

In Alzheimer’s Disease

Standardized MRI and PET acquisitionsAcross a wide network of hospitals

Quality control

A portfolio of advanced image analysis pipelinesand machine learning techniques

for biomarker research

40 engineers and

clinical research assistants


ProvidersBuffer

MRI

QC

T1 MRI

QC

Rs fMRI

QC

Diff MRI

PETQC

FDG

PET

QC

AV45

PET

QC

SPECT

CentralizedDatabase

The factoryBrainVISA

Distributed R&D

Raw

data Processed dataOne color

= IP

Data

flow


MEG 3T 7T 11.7T 17T

PETSPECT

PET / CT

1.5Tmicro PET

7T animal PET

microtome

BrainVISA

BrainVISA is the backbone of I2BM

Mutualisation


What is BrainVISA ?

A pool of development environments Mainly in Python and C++

A multi-OS compilation, documentation packaging and distribution platform

A pipeline definition framework A fully customizable data organization system A powerfull and scriptable visualization tool A portfolio of application toolboxes A conductor software for playing with data and

toolboxes


Interface to processing software

FreeSurfer

MATLAB


Pipeline definition

eNode = ParallelExecutionNode( 'SulciRecognition', parameterized = self, optional=1)

eNodeL = ProcessExecutionNode( 'recognitionInterface‘, optional=1, selected=1)

eNode.addChild("LeftSulciRecognition", eNodeL)

eNodeR = ProcessExecutionNode( 'recognitionGeneral‘, optional=1, selected=1)

eNodeR._process.name = 'Sulci Recognition (right side)'

eNode.addChild("RightSulciRecognition", eNodeR)

Sulci recognition

Left sulci recognition

Recognition interface

Left sulci recognition

Recognition interface


Parallel processing with soma-workflow

Run jobs in parallel on any distributed computing resource


Soma-workflow main features

Unified interface to many resourcesSubmission of jobs or workflows to various computing resources possibly managed by various systems (such as Grid Engine, Condor, Torque/PBS, LSF..)

Python API and Graphical User InterfaceThe GUI provides an easy and quick way of monitoring workflows on various resources.

Workflow enginehandles the execution of workflows (a set of jobs with dependencies) on computing resource according to the jobs dependencies.

Remote access to computing resourcesThe communication with the remote computing resource is done with ssh and is transparent for the user.

DisconnectionsThe client/server architecture enables the user to close and restart the client application at any time without stopping jobs execution or loosing execution status information.

File transfersIf the user’s machine and the computing resource do not have a shared file system, soma-workflow can manage file transfers between the client and the computing resource.

http://brainvisa.info/soma-workflow


soma-workflow architecture


Remote access to computing resource


Processing is not enough

Computing a lot producing a lot of data

Need to organize data and processes Definition of a Schema

Need to extract information from data and processes Definition of a request language

Need database engine implementations


Use case examples

Everyday work Apply sulci segmentation process on all T1 MRI of subjects

older than 20 from CATI database I want the result on my laptop to do manual corrections offline

and put these correction in the database later

Data or pipeline sharing Could you try your wonderful new analysis pipeline on all

subjects in my database ?

Automation of quality control Check that length of each thalamus of adult healthy subjects

segmented today are > 4 cm and < 8 cm


BrainVISA customizable data schema

Hierarchy of types Raw T1 MRI

protocolsubjectacquisitionnormalization

T1 MRI Bias Corrected:protocolsubjectacquisitionanalysis

T1 MRI:protocolsubjectacquisitionnormalizationanalysis

Attributes


Link between database and file system

bijection

Raw T1 MRI: {protocol}/{subject}/t1mri/{acquisition}/<subject> {protocol}/{subject}/t1mri/{acquisition}/normalized_{normalization}_<subject>T1 MRI Bias Corrected: {protocol}/{subject}/t1mri/{acquisition}/{analysis}/nobias_<subject>


Future CATI architecture

BrainVISA

Database API Pipeline API

Database engines Computing resources


Conclusion

BrainVISA has: a generic pipeline infrastructure a customizable data organization framework an interface for distributed computing

CATI brings manpower for BrainVISA evolutions

We are ready to be connected with the rest of the world

CATI Pitié-Salpêtrière CATI: A national platform for advanced Neuroimaging In Alzheimer’s...

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