1. CATI Pitié-Salpêtrière CATI: A national platform for advanced Neuroimaging In Alzheimer’s Disease Standardized MRI and PET acquisitions Across a wide network of hospitals Quality control A portfolio of advanced image analysis pipelines and machine learning techniques for biomarker research 40 engineers and clinical research assistants

2. CATI Pitié-Salpêtrière Providers Buffer MRI QC T1 MRI QC Rs fMRI QC Diff MRI PET QC FDG PET QC AV45 PET QC SPECT Centralized Database The factory BrainVISA Distributed R&D Raw data Processed data One color = IP Data flow

3. CATI Pitié-Salpêtrière MEG3T7T11.7T17T PET SPECT PET / CT 1.5T micro PET 7T animal PET microtome BrainVISA BrainVISA is the backbone of I2BM Mutualisation

4. CATI Pitié-Salpêtrière What is BrainVISA ? A pool of development environments A pool of development environments Mainly in Python and C++ Mainly in Python and C++ A multi-OS compilation, documentation packaging and distribution platform A multi-OS compilation, documentation packaging and distribution platform A pipeline definition framework A pipeline definition framework A fully customizable data organization system A fully customizable data organization system A powerfull and scriptable visualization tool A powerfull and scriptable visualization tool A portfolio of application toolboxes A portfolio of application toolboxes A conductor software for playing with data and toolboxes A conductor software for playing with data and toolboxes

5. CATI Pitié-Salpêtrière What is BrainVISA ? A pool of development environments A pool of development environments Mainly in Python and C++ Mainly in Python and C++ A multi-OS compilation, documentation packaging and distribution platform A multi-OS compilation, documentation packaging and distribution platform A pipeline definition framework A pipeline definition framework A fully customizable data organization system A fully customizable data organization system A powerfull and scriptable visualization tool A powerfull and scriptable visualization tool A portfolio of application toolboxes A portfolio of application toolboxes A conductor software for playing with data and toolboxes A conductor software for playing with data and toolboxes

6. CATI Pitié-Salpêtrière Interface to processing software FreeSurfer M ATLAB

7. CATI Pitié-Salpêtrière 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

8. CATI Pitié-Salpêtrière Parallel processing with soma-workflow Run jobs in parallel on any distributed computing resource

9. CATI Pitié-Salpêtrière Soma-workflow main features Unified interface to many resources Submission of jobs or workflows to various computing resources possibly managed by various systems (such as Grid Engine, Condor, Torque/PBS, LSF..) Unified interface to many resources Submission 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 Interface The GUI provides an easy and quick way of monitoring workflows on various resources. Python API and Graphical User Interface The GUI provides an easy and quick way of monitoring workflows on various resources. Workflow engine handles the execution of workflows (a set of jobs with dependencies) on computing resource according to the jobs dependencies. Workflow engine handles the execution of workflows (a set of jobs with dependencies) on computing resource according to the jobs dependencies. Remote access to computing resources The communication with the remote computing resource is done with ssh and is transparent for the user. Remote access to computing resources The communication with the remote computing resource is done with ssh and is transparent for the user. Disconnections The 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. Disconnections The 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 transfers If 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. File transfers If 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

10. CATI Pitié-Salpêtrière soma-workflow architecture

11. CATI Pitié-Salpêtrière Remote access to computing resource

12. CATI Pitié-Salpêtrière Processing is not enough Computing a lot  producing a lot of data Need to organize data and processes Need to organize data and processes  Definition of a Schema Need to extract information from data and processes Need to extract information from data and processes  Definition of a request language Need database engine implementations Need database engine implementations

13. CATI Pitié-Salpêtrière Use case examples E veryday work E veryday work Apply sulci segmentation process on all T1 MRI of subjects older than 20 from CATI database 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 I want the result on my laptop to do manual corrections offline and put these correction in the database later Data or pipeline sharing Data or pipeline sharing Could you try your wonderful new analysis pipeline on all subjects in my database ? Could you try your wonderful new analysis pipeline on all subjects in my database ? Automation of quality control Automation of quality control Check that length of each thalamus of adult healthy subjects segmented today are > 4 cm and 4 cm and < 8 cm

14. CATI Pitié-Salpêtrière BrainVISA customizable data schema Hierarchy of types Raw T1 MRI protocol subject acquisition normalization T1 MRI Bias Corrected: protocol subject acquisition analysis T1 MRI: protocol subject acquisition normalization analysis Raw T1 MRI protocol subject acquisition normalization T1 MRI Bias Corrected: protocol subject acquisition analysis T1 MRI: protocol subject acquisition normalization analysis Attributes

15. CATI Pitié-Salpêtrière Link between database and file system bijection Raw T1 MRI: {protocol}/{subject}/t1mri/{acquisition}/ {protocol}/{subject}/t1mri/{acquisition}/normalized_{normalization}_ T1 MRI Bias Corrected: {protocol}/{subject}/t1mri/{acquisition}/{analysis}/nobias_ Raw T1 MRI: {protocol}/{subject}/t1mri/{acquisition}/ {protocol}/{subject}/t1mri/{acquisition}/normalized_{normalization}_ T1 MRI Bias Corrected: {protocol}/{subject}/t1mri/{acquisition}/{analysis}/nobias_

16. CATI Pitié-Salpêtrière Future CATI architecture BrainVISA Database APIPipeline API Database engines Computing resources

17. CATI Pitié-Salpêtrière Conclusion BrainVISA has: BrainVISA has: a generic pipeline infrastructure a generic pipeline infrastructure a customizable data organization framework a customizable data organization framework an interface for distributed computing an interface for distributed computing CATI brings manpower for BrainVISA evolutions CATI brings manpower for BrainVISA evolutions We are ready to be connected with the rest of the world We are ready to be connected with the rest of the world