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UCSB Bio-imaging Infrastructure

Center for Bioimaging Informatics. www.bioimage.ucsb.edu Supported by NSF ITR #0331697. UCSB Bio-imaging Infrastructure. December 2006. Projects. Bisque/OME In use at UCSB Bisquik Next generation system (in construction). Motivation. Analysis creates knowledge Image analysis

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UCSB Bio-imaging Infrastructure

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  1. Center for Bioimaging Informatics www.bioimage.ucsb.edu Supported by NSF ITR #0331697 UCSB Bio-imaging Infrastructure December 2006

  2. Projects • Bisque/OME • In use at UCSB • Bisquik • Next generation system (in construction) December 2006

  3. Motivation • Analysis creates knowledge • Image analysis • Querying • Mining • Available Storage systems are growing • Available Processing increasing December 2006

  4. Challenges • Diverse users • UCSB Neurosciences institute • Retinal detachment : Fischer et al • Microtubule dynamics : Feinstein and Wilson • CMU Murphy Lab • Flybase • Computable Plant • Dataset challenges • Multiple types and collection techniques • Complex images (5D) and metadata • Acquisition and management of large sets • Security of private data • Sharing of experimental data December 2006

  5. Challenges • Metadata • Collection • Organization • Sharing/interpretation • Dataset management • Personal collections • Multiple organizations • Privacy and security • Analysis design • Analysis integration December 2006

  6. Block System diagram Image Analysis Browse Search Content + metadata Collection Analysis Interactive Enhancement Semantic Analysis Knowledge Discovery Image and metadata capture DB Storage Ground truth Collection December 2006

  7. BISQUEBio-Image Semantic Query User Environment • Current dataset collection • BISQUE functionality • Data management • Ground truth acquisition • Analysis • Architecture December 2006

  8. Current collections • UCSB Retinal Objects (confocal, EM) • UCSB Microtubule Objects(light, AFM) • Total estimated size in TBs and growing for 1 Lab • Complexity and analysis are the main issues December 2006

  9. Data management capabilities • Digital notebook • Direct import process • Reconfigurable (confocal, 4 x microtubule, etc) • Web • Web access and browsing • Organize images and metadata • Data sharing environment • Search by metadata or content • Integrated analysis December 2006

  10. Screenshots (Digital Notebook) December 2006

  11. Data management capabilities • Digital notebook • Capture experimental/image parameters • Direct Import process • Reconfigurable (confocal, 4 x microtubule, etc) • Web • Web access and browsing • Organize images and metadata • Data sharing environment • Search by metadata or content • Integrated analysis December 2006

  12. Screenshots (browsing) Dataset Browsing December 2006

  13. Screenshots (search) December 2006

  14. Screenshots (search) December 2006

  15. Screenshots (search similar) December 2006

  16. Screenshots (search similar) December 2006

  17. Screenshots (personal collection) Data sharing December 2006

  18. Screenshots (5D Viewer) December 2006

  19. Screenshot (5D with tracks) December 2006

  20. Image analysis • Integrated image analysis • Image enhancement • Cell counter (ImageJ) • Quantify microtubule dynamics • Microtubule tracker (manual, automatic) • Track identification • Integration in progress • Segmentation and classification • Modeling microtubule dynamics • Relevance feedback improving search December 2006

  21. Screenshots (Image Analysis) Image J Cell counter December 2006

  22. System description overview • Current dataset collection • Current functionality • Data management • Ground truth acquisition • Analysis • Architecture December 2006

  23. Hardware/software infrastructure • Hardware • 16 node Cluster • dual Intel Xeon 3GHZ • Gigabit network switch • 2 TB Storage • Software • Bisque • OME (Apache, Postgresql) • Linux December 2006

  24. Bisque ArchitectureBio-Image Semantic Query User Environment BISQUE Research in biology Distributed computing cluster image Digital Notebook XML metadata features Image/ metadata server search WEB analysis Cell counter lug-in for ImageJ Cell counter lug-in for ImageJ external internal Cell counter lug-in for ImageJ Cell counter plug-in for ImageJ XML Research in image processing and indexing December 2006

  25. OME Base • Open Microscopy Environment • “OME is an open source software project to develop a database-driven system for the quantitative analysis of biological images. OME is a collaborative effort among academic labs and a number of commercial entities”. • Provides base for image/metadata storage and analysis integration • Boston: Sorger Lab • Baltimore: Goldberg Lab • Dundee: Swedlow Lab • Madison: LOCI December 2006

  26. Bisque extensions • Ongoing extensions with OME • Content based search • Analysis integration with OME • Segmentation • Cell Counting • MT identification and Analysis • Etc. • Front end dataset and analysis support • Schema additions for image types and analysis • (Uncertainty modeling and queries) December 2006

  27. Bisque • Built 1st generation w/ >5000 5-D images • Integrated several useful analyses • Being used internally • External Interest • Immediate future • Continued development • analysis integration • Dataset integration • Remote deployments • Integration with other projects • Flybase : Integration of schema/datasets in progress • Computableplant.org December 2006

  28. Projects • Bisque/OME • In use at UCSB • http://hammer.ece.ucsb.edu/bisque • guest/bioimage • Bisquik • Next generation system (in construction) December 2006

  29. Bisque/OME lessons learned • Getting the “correct” metadata is hard • Correct may need to change or be reinterpreted • Sql schema difficult to change • Getting the “right” name is difficult • Different terms used in different labs make data integration painful • Analysis integration needs to be easy • Researcher balk at learning complex software • Users expect a rich experience • Google, flickr, etc have raised the bar December 2006

  30. New project: Bisquik • DoughDB: Flexible metadata • Ontology support • Rich user experience • Web 2.0 : Ajax, SVG • Web based tools: DN, Graphical Annotator • Programming toolkit • Smaller is better • Distributed data store • Support for large scale computation • Expected early 2007 December 2006

  31. Block Components Metadata Annotation DoughDB Metadata Renderer Permission Web UI Ontology Blob/Image Server Remote Access Analysis Engine December 2006

  32. Tagging Screen Shot December 2006

  33. Motivation: • Current metadata model is inflexible • Adding new experimental images requires: • Changes to Digital notebook • Changes to Bisque interface • Changes to OME/postgres • Shouldn’t this be easier? • “Find images tagged with rod-opsin” • “Create a region and specify the object” • “Add experimental metadata to this dataset” December 2006

  34. Bisquik requirements • Add new tag/value pairs to any db object • (Foo,2) • (visible-cell, rod) • Allow multiple tags with same value • (visible-cell, rod) • (visible-cell, muller) • Support fine-grained tag permission/visibility • Tags have creators and access control • Support update semantics & preserve history • Timestamp tags • No deletes (except under certain conditions) December 2006

  35. Bisquik: DoughDB OID4 OID1 OID2 December 2006

  36. Bisquik queries • Find objects (images) with tag “foo” • Select a.foo • Find images with name “GV100” • Select a.name = “gv100” • Find images with cellcount < 100 • Select a.cellcount < 100 • Find images with a region similar to r1 based on feature f1 • Select r.image = i and l2(r.f1, r1[ … ]) < 10 December 2006

  37. DoughDB key features • No classes or types only tag/value pairs • Open ended data model • Pair values have owner and acl • Preserves history of annotations • SQL like query language • Simple keyword queries December 2006

  38. Bisquik ontology support • “ontology is a data model that represents a domain and is used to reason about the objects in that domain and the relations between them” • Unstructured tag/value • Great for taggers • Unhappy searchers • Different labs use different terms for the same object. December 2006

  39. Bisquik ontology support • Dictionary of terms and relations • Require (or strongly suggest) that tags and value are defined before use • Drop into ontology editor when new values and tags are encountered. • Integrated into search system • Permit (or offer) ‘alias’ ‘part-of’ ‘related-to’ searches December 2006

  40. Analysis Engine • Analysis Components • Analysis Applications • Glue language: python • Component connection library • Memory for single node • MPI for cluster based execution • Execution engine • Automatic component placement • Resources and efficient communication December 2006

  41. Analysis Engine • Interfaced with DoughDB • All input/output are Pairs or objects • Application executions recorded for data provenance December 2006

  42. Bisquik interface • http://oib.ece.ucsb.edu/bisquik • Some bisque functionality • Flickr-like interface for region tagging • Pair tagging and keyword tagging • Metadata renderers • Textual (tag) • Graphical (regions, geometry, graph data) • Analysis oriented (histogram) December 2006

  43. Region Tagging screenshot December 2006

  44. Bisquik Metadata Annotation • Unified offline (Digital Notebook) and online manipulation. • Easy to build annotation forms • Allow “schema” modification “in field” • Permit annotation templates to be shared between DN and Bisquik • Graphical geometry annotator December 2006

  45. Blob Image server • Extensible server for write-once objects • Pixels, Features • Pluggable transforms/operations • Thumbnails, slices • pixel transforms (watermarks) • Graphical metadata renderers December 2006

  46. Remote Access • All basic services are web accessible: • Soap and WSDL • DoughDB, Image server, • DoughDB pairs have unique 64 bit IDs • Split between machine ID/Pair ID • All pairs are addressable • Query engine processes foreign pairs December 2006

  47. Bisquik new hardware Query Index Query Index Query Index Query Index Query Index Query Index Query Index Query Index 1TB 1TB 1TB 1TB 1TB 1TB 1TB 1TB • 10 TB disk mirrored array (20TB) • Image Server • Database (backup) server • 8-16 Query/Analysis nodes Image Server DB/Backup Server 10TB 10TB December 2006

  48. Status • Web UI • Uploading, Tagging, simple searches • DoughDB • Single node storage and queries • Analysis Engine • In design December 2006

  49. Bisque Team: August, Jiejun, Melissa,Kris Bisquik Team: Interface: August Jiejun Jaechok Analysis Engine: Kris, Mellisa, Dmitry Ontology: David(summer), Verleen(summer), Kris DoughDB: Kris,Vebjorn Conclusion December 2006

  50. Biowall December 2006

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