The cancer Biomedical Informatics Grid ca BIG In
The cancer Biomedical Informatics Grid™ (ca. BIG™): In Vivo Imaging Workspace Projects Fred Prior, Ph. D. Mallinckrodt Institute of Radiology Washington University in St. Louis
ca. BIG will facilitate sharing of infrastructure, applications, and data • • • Common, widely distributed informatics platform Shared vocabulary, data elements, data models Common standard for developing applications
In Vivo Imaging Workspace • • Project 1: Middleware Project 2: AIM: Annotation and Image Markup Project 3: Vocabulary Project 4: XIP: Extensible Imaging Platform Metadata storage formats Metadata for Images NLP Image Annotation Terminologie s & CDEs Vocabularies & CDEs Queries & Analysis Data Capture Formats & Tools Data Re-Use Applications
Search for Images Retrieve Results
• One of the goals of the In Vivo Imaging Workspace is to facilitate the increasing use of imaging based end points in clinical trials. To achieve this an easily extensible open source platform to support image analysis and visualization was defined as a key priority • The e. Xtensible Imaging Platform (XIP) is an open source environment for rapidly developing medical imaging applications from an extensible set of modular elements. • This platform will make it easier and less expensive to access specific postprocessing applications at multiple sites, simplifying clinical trials, and most importantly, increasing the uniformity of imaging and analysis. • Imaging applications developed by research groups will more easily be accessible within the clinical operating environment, simplifying workflows and speeding data processing and analysis. • Once validated, the software should be readily transitioned into products through streamlined Federal Drug Administration, (FDA), approval processes due to the reuse of already approved libraries and open source development processes.
Deliverables • XIP. rad – – Development and application build environment Extensive and extensible set of libraries for imaging and visualization Uses Open Inventor framework Includes code generating wizards to create new objects and wrap existing libraries • XIP. ws – A reference implementation of a medical imaging workstation developed using XIP. rad – Integrated via middleware into ca. GRID – Optimized to support basic cancer research use cases – Includes two key components: • XIP. app – a use case specific “plug-in” application integrated via the DICOM WG-23 Interface • XIP. host – the hosting environment that provides XIP. apps access to services such as data stores, remote processing, etc.
XIP. ws - Reference Implementation XIP. app Standard XIP Classes Custom XIP Classes API (Plug) API (Socket) XIP. host
Open Inventor • • • Open Inventor ® (http: //oss. sgi. com/projects/inventor/ ) is an object-oriented toolkit offering a comprehensive solution to interactive graphics programming problems. It presents a programming model based on the Model/View/Controller design pattern and the concept of Pipelines. C++ modules represent Engines, Nodes and Manipulators – Engines enable the creation of processing pipelines – Nodes support the concept of scene graphs, which are hierarchical structures of objects describing what needs to be visualized in 2 D/3 D – Manipulators handle input devices, measurements and coordinate transforms in response to user interaction
Integrating existing toolkits into • Automatic Wrapper generation for 2 D/3 D libraries/toolkits such as ITK and VTK – Example: ITK for image processing, segmentation, registration – User can review parsed results and choose to support only the desired data types, hide some methods, exclude some classes, etc. • • Wrappers for ITK functions such as Region Growing, Neighborhood, Isolated, Confidence, Watershed, Thresholding, Edge Detection, Laplacian, Gaussian, … Support for ITK Data Meshes and Vector Fields
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ca. Grid • Grid Infrastructure for ca. BIG • ca. Grid Components – – – Language (metadata, ontologies) Security Advertisement and Discovery Workflow Grid Service Graphical Development Toolkit (Introduce) – Efficient Bulk Data Transport (IVI middleware) – DICOM compatibility (IVI middleware)
grid. IMAGE Architecture Expose algorithms, human markup and image data as ca. Grid Services
DICOM Interoperability • Interoperability Library – Translate between DICOM and ca. BIG data models, and DICOM QR and ca. BIG query language • DICOM Data Service – Exposes existing DICOM QR aware data resources (PACS, etc) as ca. Grid compliant service • Virtual. PACS – Allows DICOM-aware clients (review workstation, etc) to access DICOM ca. Grid data services over the grid • ca. Grid-based security for data transport, authentication, and authorization
The ca. BIG AIM Project • An ontology of image annotations – An ontology defines concepts in a domain and the relationships between those concepts • An ontology of image markups • Use of controlled terminologies – Rad. Lex, SNOMED, LOINC, UCUM • Define a set of translatable standards-based representations • Implement this functionality on the ca. BIG e. Xtensible Imaging Platform (XIP)
An Image, an Image Markup and an Annotation The pixel at the tip of the arrow [coordinates (x, y)] in this image [DICOM: 1. 2. 814. 234543. 23243] represents the Ascending Thoracic Aorta [SNOMED: A 3310657]
XIP MIDDLEWARE AIM Client access Service access XIP Application XIP IDE Rad. Lex Inventor Application Modules NCI VTK Ca. BIG EVS DICOM XIP App WG 23 Grid Data Service NCIA Grid Analytical Service AIM Data Service ITK AIMTK Protégé other WG 23 System Services PLUG WG 23 System Services SOCKET DICOM OTHER GRID CLIENT SERVICES (DCMTK) OS HW Service Host IVI Middleware ca. Grid DICOM Image Sources ca. DSR, EVS, Rad. Lex, AIM ontology, etc DICOM Services
The ca. BIG 2007 Annual Meeting • February 5 - 7, 2007 • Marriott Wardman Park Hotel, Washington, DC • Plenary sessions; 60 break out sessions; exhibits, demonstrations, and posters; hackathon • Tailored sessions for newcomers February 5 and throughout the conference
- Slides: 18