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MINT Technical OverviewOctober 8th, 2010
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Agenda
• MINT Goals
• DICOM Challenges, MINT Solutions
• MINT Realized
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MINT Goals
• Improve Transfer Speed for DICOM Studies
• Eliminate need for DICOM routing / application specific caches
• Centralize QC Logic
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Typical Enterprise Architecture Today
Acquisition Device
DICOM RouterPACS
ArchiveEnterprise Viewer
Server
Advanced VisualizationWorkstation
VNA
DICOM
DICOM DICOM
DICOM DICOM
PACS Workstation
Proprietary
Enterprise Viewer
Proprietary
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Typical Viewer and Archive Architectures Today
Viewer
DICOM I/O
Processing / Clinical
Validation
Viewer (2D, 3D, etc)
HL7
Data Validation/QC/Admin
Archive (PACS, VNA, etc)
DICOM I/O
DICOM P10 Calculated Data
Storage
Data Validation/QC/Admin
Note: Many components are duplicated which creates complexity and cost
DICOM P10
Storage
Web
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DICOM Encoding
Study
Series
DICOM has a normalized data model:
But transmission is organized at theSOP Instance level:
SOP InstancePixel Data
SOP InstancePixel Data
StudySeries
SOP InstancePixel Data
SOP InstancePixel Data
StudySeries
Challenge #1:When an instance is transmitted, the study and series level informationIs 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 alwaysrequired. 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.
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DICOM TransportPACSViewer
Get Image #1
Return Image #1
….
Once all images have been received, the viewer can figure out how to display them
Get Image #2000
Return Image #2000
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
Get Image #2
Return Image #2
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MINT EncodingStudySeries
SOP Instance
Pixel DataSOP 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
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MINT TransportPACSViewer
Get Metadata
Return metadata
Once metadata is received, the viewer can figure out what images it needs
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
Get Image #1-2000
Return Images #1 - 2000
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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
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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
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MINT Study Types
Metadata
Binary Data
Metadata
Binary Data
Metadata
Binary Data
Metadata
Binary Data
DICOM
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.
MINT Study
Vendor B Proprietary
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x
Logical View of the DICOM MINT Type
Patient
Study
•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)
Metadata Binary Data
SeriesSeries
Series
SOP InstancesSOP Instances
SOP Instances
Voice Clip
Image
Private Attributes
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A Study’s HistoryTime
P10 Instance 1
Instance Sequence 1Series 1, 2 & 3
(From DICOM GW)
Instance Sequence 2Series 4
(From DICOM GW)
Metadata ItemPatient Name Change
(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
5 min 1 Hour
Patient
Instance Sequence 3Presentation State Added
(From Client)
2 Days
P10 Instance 2
P10 Instance 3
P10 Instance 4
P10 Instance 5
P10 Instance 8
P10 Instance 6
P10 Instance 7
P10 Instance 9
P10 Instance 10
P10 Instance 11
P10 Instance 12
P10 Instance 13
P10 Instance 14
P10 Instance 15
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MINT Based Enterprise Architecture
Acquisition Device
Archive
MINT PACS WorkstationMINT
Enterprise ViewerMINT
Enterprise Viewer Server
MINT
Advanced Visualization Workstation
MINT
PACS Server
MINT
Proprietary
Proprietary
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MINT Impact on both Architectures
ViewerProcessing /
Clinical Validation
Data Validation/QC/Admin
Archive (PACS, VNA, etc)
DICOM P10 Calculated Data
Storage
MINT
Viewer (2D, 3D, etc)
HTTPHTTPHTTP
Admin
HL7DICOM I/O Web