The Use of OGSA-DAI with DB2 Content Manager in the eDiaMoND Project

1
The Use of OGSA-DAI with DB2 Content Manager in
the eDiaMoND Project

• M Oevers, B Collins, A Knox, J Williams

2
Overview

• eDiaMoND the project
• Strategies for Virtualisation
• How DB2 and CM are used
• OGSA-DAI enablement of CM
• Lessons Learnt

3
eDiamond Project Announcement

• One of the pilot e-science projects is to
  develop a digital mammography archive, together
  with an intelligent medical decision support
  system for breast cancer diagnosis and treatment.
  An individual hospital will not have
  supercomputing facilities, but through the grid
  it could buy the time it needs. So the surgeon in
  the operating theatre will be able to pull up a
  high-resolution mammogram to identify exactly
  where the tumour can be found Tony Blair
  (speech to the royal society 23 may 2002)

4
eDiaMoND Partners
5
eDiaMoND Project Deliverables
Phase 0 Prototype (end-2003)
Phase 1 Prototype (mid-2004)
eDiaMoND
? (Next Phase)
BluePrint
Breast Screening Programmes

• Grid Infrastructure
• Grid-connected Workstation
• Database for Storage Retrieval of Images
  Metadata
• Computation for CADe, CADi and Statistical
  Analyses
• Required Hardware, Software Network for given
  Service Levels

6
eDiaMoND Functional Model
7
Strategies for Virtualisation
Use II II4C Expose through OGSA-DAI
Investigate DQP
8
Virtualisation things to remember

• Each Breast Care Unit (BCU) to operate
  independently from others
• Individual organisations coming together to for a
  Virtual Organisation
• Data loaded locally in each BCU
• Data is owned by the BCU
• Enable read access across all BCUs seamlessly
• Replication or Federation
• DB2 II II4C
• Remember its got to be a Grid (eScience project)
• OGSA-DAI
• Distributed Query Processing (QDP) over OGSA-DAI

9
How OGSA-DAI is used with DB2 and CM

• DB2 stores the non-image data in a structured
  form
• DICOM describes an ER model Patient Study
  Series Image
• Flexible to allow for multiple modalities
• Allow flexibility of data modelling/access
  control/query rewrite
• CM is used to store and manage the (large 30MB)
  DICOM files
• Files contain both non-image data and image data
• Identified by DICOM SOP Instance UID
• Flat CM data model (Customer Requirement)
• Both exposed as OGSA-DAI services

DICOM Digital Imaging and Communications in
Medicine
10
(No Transcript)
11
Grid Development Phase 0 to Phase1
CHU
KCL
UCL
UED
Viewer
Client Layer
Grid Layer
WORKLIST
Deploy
QUERY
RETRIEVE
Grid Layer
DB2 OGSA DAI
CM OGSA DAI
Data Layer
CM
12
CM Grid enablement What it means
OGSA-DAI conf/ext points
Mapping to CM

• Driver Class, e.g.
• com.ibm.db2.jcc.DB2Driver
• Driver URI, e.g.
• jdbcdb2//localhost50000/SAMPLE
• Connection
• DriverManager.getConnection()
• Metadata
• Table Schema for SQL
• XML schema for XML DB
• Mapping of Grid Certificates to DB user and
  password

• Datastore object, e.g
• com.ibm.mm.sdk.server.DKDatastoreICM
• Data store name, e.g.
• ICMNLSDB
• Connected Datastore
• Datastore.connect()
• Metadata
• ItemTyes and Attributes
• Could it be treated as an XML DB?
• Mapping of Grid Certificate to CM user and
  password

It was possible to map CM concepts to
corresponding JDBC concepts that are exposed in
OGSA-DAI configuration files 2 XML files to edit
and 2 Java classes to write
13
The Gory details
14
Lessons Learnt

• OGSA-DAI is a flexible framework into which CM
  fits reasonably well
• Chaining of activities
• User defined activities
• Developer focus on writing activities
• Use of dynamic discovery to configure the system
• Useful during development/testing
• Register more in the registry
• Unifies the view of the system as far as data is
  concerned
• Experience of grid-enabling an existing product
• Have not explored how to expose CM metadata yet

15
Thank You
Manfred Oevers manfred_oevers_at_uk.ibm.com
16
Data Load - High Level Design

• DICOM file gets parsed
• XML file created with Reference
• XML file passed to load services
• CM pulls DICOM file in
• As simple as possible

17
Data Load Detailed Design

• Plugin Architecture
• Decoupling
• Configuration of Plugin to decide
• Parser also pluggable
• API as simple as possible

OUCL
IBM
18
eDiaMoND API
19
eDiaMoND - Organisation
Oxford / Churchill
Edinburgh
Development (OUCL)
Aberdeen
JANET Network
Development (Mirada)
UCL / St Georges
KCL / Guys
Development (IBM)
Server
Workstation
T221
Grid Boundary
20
Federation setup DB2
DBFEDCORE Nodeedibm View cis.patient
edibm.patient union edouc.patient

• Create view over
• union of
• nicknames of
• identical tables
• No query rewrite
• necessary

Server edibm Nickname edibm.patient
Server edouc Nickname edouc.patient
DBEDCORE Nodeedibm Tablecis.patient
DBEDCORE Nodeedouc Tablecis.patient
21
The M Diagram
22
eDiaMoND Non-Functional
Anonymisation
Grid
Lossless Compression
Encryption
256MB 5 secs response
100 Centres
Systems Administration
Non-Repudiation
23
Phase 1 Deployment
CHU
MIR
GEO
JANET / Internet
JANET / Internet
T221
T221
eDiaMoND Dev. Grid Node
MIR LAN
T221
Digitiser W/S
Digitiser W/S
Digit.
Digit.
eDiaMoND Dev. W/S
UCL
UCL LAN
CHU LAN
T221
OUCL
eDiaMoND W/S
eDiaMoND W/S
T221
T221
T221
T221
eDiaMoND Grid Node
eDiaMoND Grid Node
eDiaMoND Dev. Grid Node
eDiaMoND Demo W/S
OUCL LAN
eDiaMoND LAN
eDiaMoND Test Grid Node
eDiaMoND Demo Grid Node
eDiaMoND Repository Server
KCL
UED
eDiaMoND LAN
UED LAN
GUY LAN
eDiaMoND Grid Node
eDiaMoND Grid Node
T221
eDiaMoND W/S
eDiaMoND W/S
T221
T221
IBM
T221
T221
eDiaMoND Demo. Grid Node
IBM LAN
SCO
IBM Dev. Grid Node
GUY
T221
Digitiser W/S
Digitiser W/S
Digit.
Digit.
eDiaMoND Demo. W/S
24
UK Breast Screening Challenges
Digital
Began in 1988 Women 50-70 Screened Every 3
Years 2 Views/Breast Demographic Increase 100
Breast Screening Programmes - Scotland - Wales -
Northern Ireland - England
Digital
2,000,000 - Screened every Year 120,000 -
Recalled for Assessment 10,000 - Cancers 1,250 -
Lives Saved
230 - Radiologists (Double Reading) 50 -
Workload Increase
25
Breast Cancer Facts

• 1 in 8 women will develop breast cancer in the
  course of their lives, 1 in 28 will die of it
• In the EC breast cancer accounts for 19 of
  cancer deaths and 24 of cancer cases
• Diagnosed in 348,000 women in ECUSA and kills
  115,000 women annually
• 1,000,000 new cases world-wide in 1997
• Rationale for Screening
• Early diagnosis better Prognosis
• Detection at 0.5cm has favourable outcome in 99
  cases but at 2cm only 50

26
UK Breast Screening Programme
The Recall rate is 86 for First Time Screening as
no comparison is possible with a previous
Screening
Missed 1
Interval Cancers
Cancer 6
Call 1000
Recall 40 (86)
Screening
Assessment
All Clear 960 (914)
All Clear 34 (80)
Epidemiology
100 Breast Screening Programmes
Training
27
Project Teams

• Grid Infrastructure Team
• IBM
• Oxford University Computing Laboratory
• Image Analysis Technology Team
• Dept of Engineering Science
• Mirada Solutions
• Image Collection Clinical Assessment Team
• St Georges Hospital
• Guys and St Thomas Hospitals
• Oxford Radcliffe Hospitals
• Kings College London
• University College London
• University of Edinburgh

28
SMF - Miradas Patented Standardisation Process
Mammograms have very different appearances,
depending on image settings and acquisition
systems
The interesting tissue representation is a
surface independent of scanner
29
Miradas Interesting Tissue Representation
A quantitative representation of breast tissue
density