Un sistema avanzato per la gestione di immagini biomedicali in

Un sistema avanzato per la gestione
di immagini biomedicali in ambiente
GRID
G. Aloisio
SPACI Consortium & University of Salento, Italy, Lecce
Outline
• Scenario
• Related Works
• Issues
• Medical Imaging Environment
– System Architecture
– Data Storage
– Workflow Management
– Metadata Management: GRelC
– Case Studies: CMCC & Climate-G
– Security
– Web Gateway
• Conclusions
2
Scenario, issues and needs
• Huge amount of medical data produced by several Centres (i.e. Hospitals)
• Medical Interconnection Network: data “sharing” among several centres
• Data integration, digital libraries, sharing are FP7 keywords
• Need to move towards “open”, secure, distributed and service-based environments
Patients
Challenging issues
o Security
o Data distribution
o Data format heterogeneity
o Metadata management
o Metadata schema
o Transparent access to the system
o Scalable approach
o ….
Infrastructure
Clinicians
3
Grid for Biomedical Imaging, 1999
Raw data
HPC
Pre Processing
Acquisition
Computational Grid
Globus
Server
4
Surrounding context
MediGrid
…and more…
5
Issues (high level)
• Medical images storage and processing
– TAC, MRI, fMRI, PET, SPECT
– DICOM image format
– Privacy issues
• Very large data sets handling
– storage management (PACS)
– Metadata management
– Security of data
• Process complex algorithms with large computing power and
memory requirements
– parallel processing
– workflow Management System (WFMS)
PET
TAC
MRI
SPECT
fMRI
6
AGIR - gLite based
www.aci-agir.org
7
Medicus - Globus based
http://dev.globus.org/wiki/Incubator/MEDICUS
8
Medical Imaging Environment
Info
Data Virtualization
DICOM
Images
Info
DICOM
Images
Computational
Providers
DICOM
Images
Cloud Environment
Info
Grid Environment
9
Main Issues (architectural level)
• Full security support (data security/privacy)
• Integration effort is needed to achieve high level results
• Transparent management of data & metadata
• Preservation of data locality (distribution of data)
• Distribution of metadata
• Access via Web Gateway
• Workflow management for medical purposes
• high level tools for end users
• medical imaging methods composition
• Grid support (storage, computation) on a large scale
10
Medical Imaging - Data Virtualization
Info
Data Virtualization
DICOM
Images
Info
DICOM
Images
- Distributed Data & Metadata
- Locality/Autonomy
- Scalability
- Legacy systems (PACS)
- Security
- Metadata
- DB Encryption
- Authorization/policies/roles
- Data
- Storage Encryption
- Network
- Communication protection
- Interchange Protocols
DICOM
Images
Info
11
Medical Imaging - Analysis
Data Virtualization
Info
DICOM
Images
Info
DICOM
Images
Computational
Providers
Cloud Environment
Grid Environment
Analysis
- Distributed
- Grid Based
- Cloud Based
- Complex
- Medical Workflow
- Secure
- Data anonymisation
- Data Encryption
- Authorization/Authentication
12
System Architecture
Web Gateway
Orchestrator/Collective Services
Security
Metadata
Service
Data
Service
Comput.
Service
Grid Middleware
MediGrid
Fabric Layer (data and metadata)
13
Medical imaging - Storage
• Management of Medical Images
 Secure on site management of DICOM images
 Encryption of data
 Anonymisation of data for analysis outside the centre
 Access control through authorization
 Storage interfaces between distributed environment and local
storage devices
 Secure and efficient data transport protocols
 Backup of data
 ….
14
Biomedical Imaging Processing Issues
• Huge amount of data
– 1 radiology department: 10TB/year;
– 1 CT dataset: 500MB-2GB.
• Compute-intensive analysis
– Registration noisy;
– Difficulty in the segmentation;
– Volume Reconstruction.
• Need to explore several imaging analysis algorithms, validation
methods, visualization pipelines
Data
Mng
CE
Grid
Scheduler
– Grid Workflow Management System
********************************************************************************
UNIVERSITY OF CHICAGO HOSPITALS
RADIOLOGY CONSULTATION
********************************************************************************
342 02/05/96
UNIVERSITY OF CHICAGO HOSPITALS
BHIS #: 1234567
INPATIENT
201-23-90
RADIOLOGY CONSULTATION
Hematology
/ Oncology
CHANDLER, CAROLYN
342 02/05/96
Mitchell-6NE
49
FEMALE 201-23-90
BHIS #: 1234567
INPATIENT
Hematology / Oncology
Admitting
Diagnosis: NEUTROPENIC FEVER; HYPERBILIRUBEMIA
Mitchell-6NE
Clinical data: Biliary tube check.
Carl
M. Gompers,
MD
Admitting
Diagnosis:
NEUTROPENIC FEVER; HYPERBILIRUBEMIA
Clinical data: Biliary tube check.
Change Perc
Drainage
CarlBiliary
M. Gompers,
MD Cath Proced
--
Change Perc Biliary Drainage Cath Proced
COMPARISON: 07/23/95 and 06/27/95
CHANDLER, CAROLYN
49
FEMALE
Exam #46 on 01/08/96
--
Exam #46 on 01/08/96
FINDINGS:
After the
procedure
was explained to the patient and informed
COMPARISON:
07/23/95
and 06/27/95
& Int -- Exam #47 on 02/05/96
FINDINGS: After the procedure was explained to the patient and informed
& Int -- Exam #47 on 02/05/96
FINDINGS: As above.
IMPRESSION:
FINDINGS: As above.
Successful
biliary tube change, and findings consistent with interval tumor
IMPRESSION:
growth.
Successful biliary tube change, and findings consistent with interval tumor
Simon
A. Templar, MD / Richard Nixon, MD (R19)
growth.
Signed 02/9/96 at 8:48 AM
3
Simon A. Templar, MD / Richard Nixon, MD
Signed 02/9/96 at 8:48 AM
(R19)
3
Node
15
Medical Imaging - Workflow
Info
DICOM
Images
Info
DICOM
Images
Workflow Example
Cloud Environment
Computational
Providers
Grid Environment
• Denoising
• Segmentation
• Rendering
16
Metadata on the GRID
• Metadata is data about data
• Metadata enables search and discovery
• Metadata on the GRID
– Mainly information about files
– Usually stored on DBs
• Need simple SOA & Grid interfaces for Metadata access
– Advantages
 Easier to use by clients
 Robust paradigm
 Exploiting Grid Security paradigm
 Addressing Interoperability
 17
Why are metadata so important?
• Metadata is the key to manage, route and retrieve data properly
• PACS systems can be “federated” exploiting metadata
• Search and discovery of “clinical case studies” are afforded by metadata
system
• Metadata information increases the global knowledge about available patient
data
• From data to metadata and from metadata to knowledge to support
Physicians for diagnostic and therapeutic purposes
• How to manage “efficiently”, “securely” and transparently” metadata?
METADATA SERVICE
18
Metadata Service
• Metadata service
– Compatibility with distributed systems
– Full security support for metadata
– authorization (policies, roles, etc.)
– authentication (based on grid certificates)
– Access/Integration of metadata sources
– Distributed vs centralized approach
– Suitable Metadata Schema
• Grid Access interface
– Common interface for RDBMS and XML-DB
– Database backend independence
– GSI support
19
Metadata Management: Stack
20
GRelC Project (starting date 2001)
Grid Relational Catalog (GRelC)
is a project which aims at
designing and developing a set of
efficient, secure and transparent
Data Grid Services
XML
DB
DB
DB
Grid
21
Grid Metadata Handling System: architecture in the small
GRelC DAIS
22
International Testbeds
sepac00.projects.cscs.ch
Linux x86
Lecce (Italy)
GRelC Data Access
Data Sources (DB)
Bejing
(China)
gandalf.unile.it
Linux x86
spacina.na.infn.it
Linux IA64
sara.unile.it
Mac OS X
sigma2.unile.it
Linux IA64
gridsurfer.unile.it
FreeBSD
galileo.hpcc.unical.it
Linux IA64
23
Test Performance
SQ comparison (Beijing - Lecce) - large
450
400
350
300
250
MEMORY
DIME
DIME+ZIP
STREAM
PSQL
time (sec)
200
150
100
50
0
10000
50000
tuples (n)
100000
24
CMCC: a fully distributed data grid environment
Grid Layer
- VOMS Server
- CMCC Data Grid Portal
- Metadata Server (GRelC DAIS)
- Grid Storage
- GridFTP
- GRelC Storage
- CMCC CA
- P2P layer
Data and Metadata resources
- RDBMS (Oracle,MySQL, Postgres)
- XML DBs (eXist, XIndice, etc.)
Grid SS
Grid SS
Grid SS
Search & Discovery
- Two step process
25
A new research effort: Climate-G
The main goal of Climate-G is to create a unified environment for
climate change, able to concentrate in the same context big amount
of data geographically spread among several centres, rich metadata
descriptions, efficient data access services, advanced data analysis
and visualization tools, etc. exploiting and joining knowledge and
skills in the fields of climate change and computational science
26
Climate‐G
partners
Università del Salento
27
Metadata Distribution and virtualization
For each site:
Relational DB (index)
XML DB (entire schema)
Virtualization/Integration layer:
GRelC DAIS
Virtualization allows to conceal:
Data distribution
Number of sites,
RDBMS and XML back-ends
P2P Topology
Data Integration aspects
technological details
…
28
Security
What
about
security?
– Authen'ca'on
(mutual
process)
– Authoriza'on
– Access
control
lists
– Role
Membership
Services
– Data
encryp'on
(to
ensure
secure
data
communica'on)
– Data
anonymisa'on
(to
move
data
outside
the
Centers)
– A
cer'ficate
for
each
actor
(user,
service,
host)
– Each
ac'on
is
associated
with
an
actor
– Firewall
protec'on
– …
29
Medical Web Gateway
• Main Functionalities
o Search & Discovery
o Data access & viz
o Workflow management
o Users and roles mng
o ….
• Features
o Easy to use interfaces
o Platform independent
o Secured by design
o Integrated environment
o Data and …
o Analysis tools
o Visualization tools
o Post-processing tools
30
Medical Imaging Environment
Info
Data Virtualization
DICOM
Images
Info
DICOM
Images
Computational
Providers
DICOM
Images
Cloud Environemnt
Info
Grid Environment
31