Collaborations and Architectures mBIRN Progress at BWH.

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Collaborations and Architectures mBIRN Progress at BWH

Transcript of Collaborations and Architectures mBIRN Progress at BWH.

Page 1: Collaborations and Architectures mBIRN Progress at BWH.

Collaborations and Architectures

mBIRN Progress at BWH

Page 2: Collaborations and Architectures mBIRN Progress at BWH.

BWH mBIRN Accomplishment Highlights

• Protocol-Neutral Segmentation with MIT– EM Brain Atlas Classifier hierarchical joint segmentation/registration tool– Lesion segmentation now available (used for MS)

• Facial Segmentation (BIRNDUP) with MGH– BIRNDUP Application Ready, Shown at Sedona– IRB Review of Defacing underway

• DTI Analysis– Data Format Standardization– Powerful Visualization and Analysis Tools: Registration, Cluster Atlas

• Shape Visualization: Awaiting refinement of clinical needs• Integrated Visualization

– “Slicer3” is Major Redesign to Support Interactive and Batch Processing– Modern Software Engineering Methodology– FreeSurfer Interoperability

• Query Atlas– New Slicer3-based framework– Structure/Function integration with Databases and BIRN Tools

• Portal Integration– Ongoing work with BIRN-CC, mBIRN, fBIRN Informatics Groups on to automate data

retrieval (XNAT, HID, SRB, S3/EC2)

Page 3: Collaborations and Architectures mBIRN Progress at BWH.

Example Uses of BIRN at BWH

• DTI Clustering MIT/BWH– JHU DTI data used by Lauren O’Donnell to test Multi-

Subject DTI Automated Atlas Generation

• DTI Registration TU-Delft/BWH– JHU DTI data used by Matthan Caan for non-linear

registration based on FA– Applied to Schizophrenia subjects by KangUk Lee of BWH

• DTI Aniostropy Creases BWH/Utah

– JHU Data used by Gordon Kindlmann for automatic delineation of anatomical discontinuities

• Well Curated, High Quality, Shared Data Promotes Research!

before affine nonlinear

Page 4: Collaborations and Architectures mBIRN Progress at BWH.

BIRN Enabled BWH Collaborations

• National Alliance for Medical Image Computing (NA-MIC, Kikinis)– NIH Roadmap Effort to Promote Best Practices in Open Source

Software Engineering Methodology for Medical Imaging– Emphasis on Facilitating use of Novel Algorithms by Clinical

Researchers– Reengineered 3D Slicer is Major Deliverable (Slicer3)– BIRN Provides Pipeline, Grid Data/Compute

• National Center for Image Guided Therapy (NCIGT, Jolesz)– NCI/NCRR/NIBIB Imaging and Computing for Surgery and

Interventions– Slicer3 is Major Imaging Platform

• Neuroimage Analysis Center (NAC, Kikinis)– Algorithms and Software Incubator for Neuroimaging– Source of Novel Techniques that are Adapted and Applied to BIRN

• Many One-to-One Collaborations with non-BIRN Sites rely on BIRN Infrastructure (Data Grid, Network, Compute Resources)– GE, Kitware, Inc., JHU CISST, CIMIT, SCI, CHB…

Page 5: Collaborations and Architectures mBIRN Progress at BWH.

BWH Tools, Datasets, Studies…

• 3D Slicer Version 2.6 Includes Major BIRN Developments– EM Segmenter (low-level configurability)– EM Brain Atlas Classifier (ease of use)– DTMRI

• NRRD I/O• Clustering• ROI Tractography• FA-based Registration

– QueryAtlas Prototype– BIRNDUP Application Support– FreeSurfer Interoperability (input, output, volumes, surfaces, annotations)

• 3D Slicer Version 3 (in development)– Modern, Easily Extensible Architecture– Dynamic Query Atlas Interaction– Native FreeSurfer Support– Migration of Slicer 2.6 Functionality to Slicer3 Ongoing

• Open Source, No Restrictions on Use• Workshops, Tutorials, Data Sets available at the Slicer 101 page

– http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101– Includes structural, fMRI, DTI data; detailed data import and use instructions;

example analysis scenarios, and more…

Page 6: Collaborations and Architectures mBIRN Progress at BWH.

• Included in the current 3D Slicer 2.6 • Applied to white matter lesion segmentation in Multiple Sclerosis. • MPRAGE and FLAIR• Available to support BELL • Data courtesy Istvan Csapo, Charles Guttmann, Center for Neurological Imaging, Brigham and Women’s Hospital. Algorithm by Kilian Pohl, MIT/BWH/Isomics

EM Segmenter: enabled by the Protocol Neutral Segmentation aims of the mBIRN

Page 7: Collaborations and Architectures mBIRN Progress at BWH.

BWH User ROI Guided DTI Tractography

Input Tracts + ROIs Uncinate FasciculusInferior Occipital

Frontal Fasciculus

• Convolution-Based Tract Identification for Atlas Building• Driven by mBIRN User Requests (UCI)• Included in the current 3D Slicer 2.6• Data courtesy of Marek Kubicki and Martha Shenton, Psychiatry Neuroimaging laboratory, Brigham and Women’s Hospital. Algorithm by Raul San Jose, BWH.

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BIRN Query Atlas in Slicer3

• Re-Architecture of the QueryAtlas

– Advanced Label Features Built-In

– Real-Time Interaction with Labels

– “Right Click” on Models and Images to Initiate Queries

– Based on NA-MIC Software Engineering Methodology

– Anatomy-Based Access to Web Resources

• Integrates with BIRN IT Efforts

– Auto Convert and Load BIRN Data

• Leverages mBIRN Data Formats and Analysis (FreeSurfer)

• fBIRN is Building Functional QueryAtlas Integrated with mBIRN QueryAtlas