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MINT Technical Overview October 8 th , 2010

MINT Technical Overview October 8 th , 2010 . Draft. Agenda. MINT Goals DICOM Challenges, MINT Solutions MINT Realized. MINT Goals. Improve Transfer Speed for DICOM Studies Eliminate need for DICOM routing / application specific caches Centralize QC Logic.

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MINT Technical Overview October 8 th , 2010

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  1. MINT Technical OverviewOctober 8th, 2010 Draft

  2. Agenda • MINT Goals • DICOM Challenges, MINT Solutions • MINT Realized

  3. MINT Goals • Improve Transfer Speed for DICOM Studies • Eliminate need for DICOM routing / application specific caches • Centralize QC Logic

  4. Typical Enterprise Architecture Today Enterprise Viewer Acquisition Device PACS Workstation Proprietary DICOM Proprietary Enterprise Viewer Server DICOM Router PACS Archive DICOM DICOM DICOM DICOM VNA Advanced Visualization Workstation

  5. Typical Viewer and Archive Architectures Today Viewer (2D, 3D, etc) Archive (PACS, VNA, etc) Viewer DICOM I/O DICOM I/O HL7 Web Data Validation/ QC/Admin Data Validation/QC/Admin Processing / Clinical Validation Storage Storage DICOM P10 Calculated Data DICOM P10 Note: Many components are duplicated which creates complexity and cost

  6. DICOM Encoding DICOM has a normalized data model: But transmission is organized at the SOP Instance level: Study Study Study Series Series SOP Instance SOP Instance Series Pixel Data Pixel Data SOP Instance SOP Instance Pixel Data Pixel Data Challenge #1: When an instance is transmitted, the study and series level information Is denormalized (replicated) in each SOP Instance. This causes validation problems Challenge #2: There is no way to access the metadata (non pixel data) without pulling the pixel Data. The pixel data is 99% of the size of the study, yet not all pixel data is always required. The viewer usually needs access to all metadata to understand the study. Challenge #3: DICOM uses a custom encoder that requires a special library to understand.

  7. DICOM Transport Viewer PACS Get Image #1 Return Image #1 Get Image #2 Several minutes over Gig/E Return Image #2 …. Get Image #2000 Return Image #2000 Once all images have been received, the viewer can figure out how to display them Challenge #4: DICOM is a chatty protocol which prevents it from fully utilizing the bandwidth available in high speed networks Challenge #5: The DICOM protocol is specific to medical imaging and does not benefit from the ongoing technology advances found in standard protocols like HTTP

  8. MINT Encoding Study Pixel Data Series SOP Instance SOP Instance Pixel Data Benefit #1: MINT matches the DICOM logical model which is normalized – no data is duplicated Benefit #2: MINT allows access to the metadata independently from the pixel data Benefit #3: MINT encodes the metadata in XML – the enterprise standard for encoding information

  9. MINT Transport Viewer PACS Get Metadata Several seconds over Gig/E Return metadata Once metadata is received, the viewer can figure out what images it needs Get Image #1-2000 Return Images #1 - 2000 Benefit #4: MINT can fully leverage high speed networks by supporting batch requests. Individual images can also be requested (batch of size 1) to support streaming or on demand use cases Benefit #5: MINT leverages HTTP – the enterprise standard technology for information transport. This allows it to benefit from related technology advances and general understanding by IT

  10. Other MINT Features • Basic search capabilities • Client can search on specific keys • Not intended to directly support workflow • Changelog mechanism • Client can determine what has changed on a MINT server (new studies, images added, etc) • Support for proprietary data • Client can store proprietary data (e.g. volumes, snapshots, etc) • Data Dictionary • Stores the schema for each study type including normalization rules • Support for modifying studies • Add, update, delete normalized entities

  11. MINT Realized • Improve Transfer Speed for DICOM Studies • Leverage HTTP • Separate metadata from pixel data • Batch and streaming mechanisms for pixel data • Eliminate need for DICOM routing / application specific caches • Storage of non DICOM (proprietary) objects at the study level • Changelog simplifies synchronization • Query mechanism supports common on demand loading strategies • Centralize QC Logic • Normalized entity modification mechanism simplifies this • Elimination of data caches results in updates only needing to take place in one location

  12. MINT Study Types MINT Study Metadata Metadata Binary Data Binary Data Vendor B Proprietary DICOM Metadata Metadata Binary Data Binary Data Vendor A Proprietary AIM MINT is based on an extendable type system that is study oriented. One of the standardized MINT types is DICOM which specifies a mapping from DICOM to MINT encoding. Proprietary types can be added to store application specific data such as vendor specific 3D Volumes, XML documents, AIM documents, etc.

  13. Logical View of the DICOM MINT Type • Metadata • Includes all non binary attributes found in all DICOM SOP instances in a given study • Normalized attributes according to DICOM Information Model • Is accessed independently from the binary data • References binary data items using their id • Binary Items • Can be retrieved in batch or individually • Are identified by study scoped ids (bids or binary ids) x Voice Clip Private Attributes Image Patient Study Series Series Series SOP Instances SOP Instances SOP Instances Binary Data Metadata

  14. A Study’s History Time 5 min 1 Hour 2 Days P10 Instance 1 P10 Instance 9 Patient P10 Instance 15 P10 Instance 2 P10 Instance 10 P10 Instance 3 P10 Instance 11 P10 Instance 4 P10 Instance 12 P10 Instance 5 P10 Instance 13 P10 Instance 6 P10 Instance 14 P10 Instance 7 P10 Instance 8 Instance Sequence 1 Series 1, 2 & 3 (From DICOM GW) Instance Sequence 2 Series 4 (From DICOM GW) Metadata Item Patient Name Change (From Client) Instance Sequence 3 Presentation State Added (From Client) • Studies are not created at one single point in time • New SOP Instances may be added to a study at any time • Changes to existing instances may be made at any time • Applications may add proprietary data to a study at any time

  15. MINT Based Enterprise Architecture Acquisition Device PACS Workstation MINT MINT Enterprise Viewer Archive MINT Proprietary MINT PACS Server Proprietary MINT MINT Enterprise Viewer Server Advanced Visualization Workstation

  16. MINT Impact on both Architectures Viewer (2D, 3D, etc) Archive (PACS, VNA, etc) Viewer DICOM I/O HL7 Web Data Validation/QC/Admin Admin Processing / Clinical Validation HTTP HTTP HTTP MINT Storage DICOM P10 Calculated Data

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