OpenStack in Action 4! Susheel Varma - VPH-Share: Patient-Centred Multi-scale Cloud-enabled...

Reproducibility a principal driver of the

scientific method

Patient Centred Multi-Scale Cloud-Enabled Computational Workflows

Dr Susheel Varma University of Sheffield

3 #OIA4 Paris, France 04-‐Dec-‐13

in silico Medicine

“…is the direct use of computer simulation in the diagnosis, treatment, or prevention of a disease.”

Predict disease Personalise treatment

4 #SummerSchool 20-‐Jun-‐13 Cloud Platform

(Public / Private)

Patient Data Workflow Inputs

Workflow Outputs

Semantic Services

Patient Centred Computational Workflows

Patie

nt A

vata

r

App

licat

ion

Info

stru

ctur

e

HPC Infrastructure (DEISA / PRACE)

Pers

onal

ised

M

odel

Knowledge Discovery Data Inference

Compute Services

Storage Services

Knowledge Management

Data Services: Patient/Population

euHeart @neurIST

VPH OP ViroLab

Project No: 269978 VPH-Share

Partners: CYFRONET, PL Sheffield Teaching Hospitals, UK ATOS Origin, ES Kings College London, UK Empirica, DE CiNECA, IT Nine Health CIC, UK INRIA, FR IOR, IT Open Univ., UK Philips Elec., NL TU Eindhoven, NL Univ. Auckland, NZ Uv Amsterdam, NL UCL, UK Univ. Vienna, AT AATRM, ES FCRB, ES

Co-ordinator: University of Sheffield, UK

Select Workflow Retrieve ExisGng Data

Transform or Infer Data

Run Workflow

Return Results

VPH-Share A0 Master Plan


ATM

Atmosphere Cloud Platform

Atomic Service Deployment Wizard

MAFEventBus

Authentication Services Workflow

Execution Service

Workflow Registry

Atomic Service Registry

Atomic Service Manager Data Browser Atomic Service

Generic Invoker

Master Interface

Cloud Facade

Visualisation Tools Workflow Composer

VPH-

Share

Client

Generic Workflow Documen

t

Atomic Service

Description

Cloud Clients

libcloud

provider

libcloud

provider

Monitoring Controller

High PerformanceExecution Engine (AHE)

Extension Points

SPRUCE

HARC

Steering

AHE Services API

AHE Runtime

AHE Engine

App Regis

try

JBPM

Workflow &

Main Logic

AHE Database Hibernate ORM

App State Objec

t

Storage Module

Connector Module

External Data

Storage

External HPC

Platform

Security Module

Allocation Management Service

AMS Manag

er (Java) OSGi

bundles

Apache

Karaf

Scheduler / Optimizer

… Algo n Algo 1

REST API & HTML Service

(Ruby) Sinatra & Passenger

Domain Model (Ruby)

Atmosphere Internal Registry

MongoDB

Virtual Machine Template Registry

Data Buckets (C-DISC, CSV,

…)

Databases (SQLServer, …)

External Structured

Data Providers

Data Publishing

Suite (GUI)

Schema Crawler

SPARQL Discovery

Browser Search

RDB2RDF Service

…

LOD Databases

Silk, LinQuer Service

…

LD Databases

Multi-Ontology/Archetype

Search Services

Taverna Server

Service Registry

Load Balancer

Proxy Controller

Data Reliability & Integrity Services

PSLoader

External Cloud Data

Storage

Semantic Services

VoID Document Database

Database 1 Query Services

(SPARQL & SQL)

Database Services

Integration Points


(SPARQL & SQL)

Database n Query Services

(SPARQL & SQL)

Individual Relational Databases

VoID Services

……

……

VoID Document


Monitoring System

Atomic Service Instance Contents

Raw Operating System (Linux)

LOBCDER Federated Storage Access

Root Volume

VPH-Share Tool / App

Web Service Wrapper Soaplab2, CXF, soap4r Remote

Access Service

Web Service Security Agent

Monitoring Agent (Munin)

Hypervisor

Driver

Manager

Compute Worker

Network Worker

Object Storage (Swift)

Dashboard

Queue Scheduler

Proxy

Account

Container

Object

ASIProxy

Private Compute & Storage Cloud (OpenStack Example)

Data Volume

Data Resource Catalog

LOBCDER Data Federation Middleware

Data Stores

Connection Module

…

Request Manager

Access & Control Frontend

Virtual Resource System

… Driver 1 Driver n Cloud Storage Driver

Data Infrastructure Services

Images

NOVA API

6

Multi-Scale Scientific Workflows

#OIA4 Paris, France 04-‐Dec-‐13

Multi-Scale Challenges

•  State Space Explosion

•  Inverse Parameter Identification

•  Parameter Sensitivity

•  Incomplete Inputs

•  Strong Spatio-Temporal Coupling

•  Chaos and Unstablility

•  Uncertainty Cascade



VPH-Share Flagship Workflows

euHeart 16 Partners € 19.05 million Jun 08 – Nov 12

SoMware VisualizaGon

MulG-‐scale Models Imaging MulGmodal AcquisiGon

RegistraGon Anatomical

PaGent Therapy

Geometry

FuncGonal

Microstructure

Vasculature Coronary Flow Perfusion

Mechanics AcGvaGon

EC Cell Ventricular Flow

Ontologies

CellML

FieldML

X-‐Ray/MR MoGon

Electrical/MR ExcitaGon GIMIAS

CMGUI

Modelling tools and technologies

PaGent

ComputaGonal OpenCMISS SOFA OPENFEM LIFEV Numerical basis reducGon, POD FEM, FD, ALE Parallel CompuGng PETsc, MUMPS Data assimilaGon unscented Kalmann filtering variaGonal approaches

Current PracGce Conges(ve Heart Failure


euHeart Simulation Workflow


@neurIST Simulation Workflow

15

Medical image

Input: DICOM Output: 3D image DescripGon: Converts a DICOM image to VTK image

Segmenta(on

Input: Image,ROI Output: surface mesh DescripGon: vessels and aneurysm extracGon

Mesh Edi(ng

Input: surface mesh Output: surface mesh DescripGon: clipping vessels, cleaning surface (cell removal, closing holes, smoothing…)

Skeletoniza(on

Input: surface mesh. Output: skeleton. DescripGon: necessary to set the boundary condiGons

Aneurysm isola(on

Input: surface mesh Output: surface mesh DescripGon: aneurysm isolaGon

Morphology Descriptors

Input: surface mesh Output: xml, vtk DescripGon: surface, depth… and ZMI calculaGon

Volumetric Mesh

Input: surface mesh Output: volumetric mesh DescripGon: creates a volumetric mesh of the selected geometry

Flow Simula(on

Input: volumetric mesh, ccl Output: wall shear stress map DescripGon: solves flow equaGons

Flow Simula(on post-‐processing

Input: wall shear stress Output: .csv file DescripGon: computes hemodynamic descriptors

CFD preprocessor

Input: xml, surface mesh Output: surface mesh, ccl DescripGon: Defines hemodynamic model

Input: surface, 1D model Output: xml, vtk DescripGon: boundary condiGons for CFD

Selec(ng Boundary Condi(ons

Neck Selec(on

Input: surface mesh Output: surface mesh DescripGon: aneurysm neck surface and dome selecGon

GIMIAS

@neuFuse

ANSYS (ICEM)

ANSYS (CFX)

Manual interacGon Common opera(ons

Morphological analysis

Hemodynamic analysis


•  Gathered: scattered across different repositories/catalogues

•  All necessary elements available and accessible maybe open

•  Documented sufficiently well – Explicitly Transparent: How, Why, What,

Where, Who, When – Comprehensive: Just Enough – Comprehensible: Independent

understanding •  Skills and resources to repeat

–  Crowd sourced? Supercomputer?

PublicaGon

Models, Techniques, Algorithms

Data

Provenance AgribuGon Credit

Context InvesGgaGon

Study Assay


PublicaGon

Models, Techniques, Algorithms

Data

Provenance AgribuGon Credit

Context InvesGgaGon

Study Assay

Accessible Capable Reusable

INSTRUMENTs Samples,Specimens Strains

74% / 26%

31% / 8%

19

Embodying a Patient Avatar



•  A large virtual catalogue of every item of data, information & knowledge of •  Patient; or •  Collection of patients

(Avatars)

•  It also needs to be shared securely, to be able •  To be Searched, Browsed &

Analysed •  For Healthcare, Research &

Education

Vital Signs

Medical Devices

Results

Patient History

Procedures

Medical Images

Histology

Genomics

Proteomics

Patient Avatar

Patient Avatar – Goals •  Integrating fragmented data and knowledge into a single

cohesive unit of data

•  Creating a centralised repository with reliable population and patient data around which VPH tools and applications could be built

•  Providing diagnostic or prognostic decision and treatment planning support using predictive models built around a patient-specific avatar

•  Providing a comprehensive overview of a patient with missing data based on averages from population phenotype to explore and test ideas virtually


Current Access to Clinical Data


Owner or Facilitator Description Number (records) Accessibility

Sheffield Teaching Hospitals

ACS data Clinical data, outcomes ~750 Philips

Others on request

Nine Health HES extract Data catalogues ~ 5 millon On demand

FRCB Clinical data Ethics approved for entire record On demand

AATRM Images ~ 6 million On demand

@neurIST Image data CRIM data

Derived data

~100 (600) ~1400 ~300

On demand

euHeart 3D Models 216 cardiac ~90 other Registered users

Virolab Rule database Publication corpus

4 Rule DBs ~1.2 GB Registered users

VPH-OP Extensive clinical baseline data Images

281 Mixed On demand

23

Knowledge Management, Discovery & Semantic Services


Health Language Terminology


Health Language Terminology Terminology Sets •  SNOMED CT / CA extensions •  ICD-9P&CM •  ICD-10 •  ICD-10-CM / PCS •  CPT-4 •  HL7 •  HCPCS •  APC, DRG, MS-DRG •  LOINC •  ICPC1&2 •  DSM IV •  MeSH •  Pharmacy (FDB, Multum) – NDC •  RxNorm •  Nursing (NIC, NOC, NANDA) •  LCD/NCD/NCCI •  Consumer Friendly Terminology (CFT)

•  CDT •  Multiple Languages •  Local Codes •  Nomenclature •  ICD-10 (GM/AM/CA) •  ICD-O •  UK Admin Extension •  UK Gap Extension •  HRG •  OPCS-4 •  CCI •  Read 2 •  Read 4-byte •  SNOMED Facets •  Clinical Specialty Subsets

Mappings •  SNOMED CT to ICD-9-CM •  SNOMED CT to ICD-10 •  SNOMED CT to OPCS-4 •  ICD-9-CM to SNOMED CT •  SNOMED CT to CPT •  CPT to SNOMED CT •  ICD-9-CM to ICD-10-CM/

PCS •  ICD-10-CM/PCS to ICD-9-

CM •  SNOMED to MeSH •  DSM IV to SNOMED •  ICD-9-CM Procedures to

SNOMED •  HL7 to CHI •  Language to Language

(e.g., English to Spanish)

Web of Semantically Linked Data



Tabular Data

Non-Tabular Data

Clinical Information Systems

Data Publishing Suite

Semantic Services

Computational Workflows and Services 1

2

3 4 8 9 10 6 7

Medications

Vital Signs

Lab Reports

Demographic

Vital Signs

Images

Demographic

Risk Factors

Genomic Data

Parameter Estimation

Uncertainty Propagation

Patient Avatar

RDF Graphs

Reference Data

Pseudo Identifier (UID)Demographics

HeightWeight

Vital SignsHeart RateBlood Pressure

Systolic Diastolic

Aneurysm Related Health EventRisk FactorsAneurysm Imaging StudyMedications


HeightWeight


Systolic Diastolic

Pulmonary FunctionRisk FactorsCardiac Imaging StudyMedications


HeightWeight


Systolic Diastolic

Orthopaedic Health EventGynaecological InformationBone Phenotype Imaging StudyMedications Physiological

Envelope


Patient Avatar & Workflow Archetypes

Baseline HistoryCardiac Health EventLab TestsMedicationsCardiac Imaging StudyImaging Details

(c) euHeart Workflow Archetype

Sexual HealthHIV Subtype InformationSpecimens

(d) ViroLab Workflow Archetype

Aneurysm Related Health EventSupporting Risk FactorsSpecimens (Blood, Tissue)MedicationsAneurysm Imaging StudyImaging Details

(b) @neurIST Workflow Archetype

Hand Grip StrengthOrthopeadic Health EventMedicationsSpecimens (Blood, Tissue)Bone Phenotype Imaging Study

(e) VPHOP Workflow ArchetypePatient Pseudoidentifier (PID)DemographicsPersonal & Social HistoryFitness & LifestyleEmployment DetailsVital SignsSubstance Use

(a) Common Shared Archetype





































Knowledge Management


29

Cloud-Enabled Computational Workflows


Cloud-Enabled Computation Workflows •  portal.vph-share.eu – Provides access to Clinical Data and Scientific applications

and workflows

•  Taverna Workbench – Provides Desktop tool for composition of Scientific Workflows with VPH-Share applications and data

•  OnlineHPC.com – Allows the creation of Scientific Workflows composed of External and VPH-Share Applications and VPH-Share data

•  Meta-Workflow Manager – Executes multiple Scientific Workflow Engines on the VPH-Share Platform

•  Workflow Cloud Plugin – Allows execution of Scientific Web-Services and Application on multiple cloud platforms

•  Command-Line Wrapper – Allows developers to wrap command-line applications into a (REST/SOAP) webservice via wsme and GIMIAS

•  NoMachine RDP – Provides Remote Desktop services for applications that require user interaction


Cloud-Enabled Computation Workflows



Clinical Researcher

Workflow Manager API

VPH-‐Share plugin

Taverna Server

VPH-‐Share Workflow

Cloud Façade

Web-‐based Remote Desktop

AS without interacGon

AS with interacGon

CLIENT-‐SIDE SERVER-‐SIDE

AS AS

AS

AS AS AS

External ApplicaGon

STORAGE

VPH-‐Share plugin

Taverna Workbench

Web services

GIMIAS CLPs

…

VPH-‐Share plugin

Taverna On-‐line

Web services

…

33

VPH-Share HPC & Cloud Platform


Scientific Cloud Platform


ATM


Atomic Service Deployment Wizard

MAFEventBus

Authentication Services Workflow

Execution Service

Workflow Registry

Atomic Service Registry

Atomic Service Manager Data Browser Atomic Service

Generic Invoker

Master Interface

Cloud Facade

Visualisation Tools Workflow Composer

VPH-

Share

Client

Generic Workflow Documen

t

Atomic Service

Description

Cloud Clients

libcloud

provider

libcloud

provider

Monitoring Controller

High PerformanceExecution Engine (AHE)

Extension Points

SPRUCE

HARC

Steering

AHE Services API

AHE Runtime

AHE Engine

App Regis

try

JBPM

Workflow &

Main Logic

AHE Database Hibernate ORM

App State Objec

t

Storage Module

Connector Module

External Data

Storage

External HPC

Platform

Security Module

Allocation Management Service

AMS Manag

er (Java) OSGi

bundles

Apache

Karaf

Scheduler / Optimizer

… Algo n Algo 1

REST API & HTML Service

(Ruby) Sinatra & Passenger

Domain Model (Ruby)

Atmosphere Internal Registry

MongoDB

Virtual Machine Template Registry

Data Buckets (C-DISC, CSV,

…)

Databases (SQLServer, …)

External Structured

Data Providers

Data Publishing

Suite (GUI)

Schema Crawler

SPARQL Discovery

Browser Search

RDB2RDF Service

…

LOD Databases

Silk, LinQuer Service

…

LD Databases

Multi-Ontology/Archetype

Search Services

Taverna Server

Service Registry

Load Balancer

Proxy Controller

Data Reliability & Integrity Services

PSLoader

External Cloud Data

Storage

Semantic Services

VoID Document Database


(SPARQL & SQL)

Database Services

Integration Points


(SPARQL & SQL)

Database n Query Services

(SPARQL & SQL)

Individual Relational Databases

VoID Services

……

……

VoID Document


Monitoring System

Atomic Service Instance Contents

Raw Operating System (Linux)

LOBCDER Federated Storage Access

Root Volume

VPH-Share Tool / App

Web Service Wrapper Soaplab2, CXF, soap4r Remote

Access Service

Web Service Security Agent

Monitoring Agent (Munin)

Hypervisor

Driver

Manager

Compute Worker

Network Worker

Object Storage (Swift)

Dashboard

Queue Scheduler

Proxy

Account

Container

Object

ASIProxy

Private Compute & Storage Cloud (OpenStack Example)

Data Volume

Data Resource Catalog

LOBCDER Data Federation Middleware

Data Stores

Connection Module

…

Request Manager

Access & Control Frontend

Virtual Resource System

… Driver 1 Driver n Cloud Storage Driver

Data Infrastructure Services

Images

NOVA API

Platform Architecture


Physical resources

Atomic Service Instances Deployed by AMS on available resources as required by WF mgmt or generic AS

invoker

Raw OS (Linux variant)

LOB Federated storage access

Web Service cmd. wrapper

Generic VNC server

VPH-Share Tool / App.

DRI Service

Atmosphere persistence layer (internal registry)

VM templates

AS images

Available cloud

infrastructure

Managed datasets

101101 011010 111011

101101 011010 111011

101101 011010 111011

AM Service

LOB federated storage access

Cloud stack clients

HPC resource client/backend

Data and Compute Cloud Planorm

VPH-‐Share Master UI

AS mgmt. interface

Generic AS invoker

ComputaGon UI extensions

Data mgmt. interface

Generic data retrieval

Data mgmt. UI extensions

Remote access to Atomic Svc. UIs

Custom AS client

Workflow descripGon and execuGon

Developer ScienGst

Admin

Security mgmt. interface

Security framework

Web Service security agent

Modules available in first prototype

Cloud Platform Architecture


VPH-‐Share Master Int.

Admin Developer ScienGst

Development Mode

VPH-‐Share Core Services Host

ComputaGonal Cloud Site

Worker Node

Worker Node

Worker Node

Worker Node

Worker Node

Worker Node

Worker Node

Worker Node

Head Node

Image store (Glance)

Cloud Facade (secure

RESTful API )

Atmosphere Management Service (AMS)

Cloud stack plugins (JClouds)

Atmosphere Internal

Registry (AIR)

Cloud Manager

Generic Invoker

Workflow management

External applicaGon

Cloud Facade client

•  The platform provides a set of APIs for the VPH-Share Master Interface and other applications, enabling Atomic Services to be developed.

Customized applicaGons may directly interface the Cloud Facade via its RESTful APIs

Accessible HPC Execution Platform


�  Provides virtualized access to high performance execuGon environments �  Seamlessly provides access to high performance compuGng to workflows that

require more computaGonal power than clouds can provide �  Deploys and extends the ApplicaGon HosGng Environment – provides a set of web

services to start and control applicaGons on HPC resources

GridFTP AHE Web Services

(RESTlets)

Grid resources running Local Resource Manager (PBS, SGE, Loadleveler etc.)

ApplicaGon HosGng Environment Auxiliary component of the cloud planorm, responsible for managing access to tradiGonal (grid-‐based) high performance compuGng environments. Provides a Web Service interface for clients.

Invoke the Web Service API of AHE to delegate computaGon to the grid

ApplicaGon -‐-‐ or -‐-‐

Workflow environment

-‐-‐ or -‐-‐

End user

Present security token (obtained from authenGcaGon service)

Tomcat container WebDAV

User access layer

QCG CompuGng

Job Submission Service (OGSA BES / Globus

GRAM) RealityGrid SWS

Resource client layer

Delegate credenGals, instanGate compuGng tasks, poll for execuGon status and retrieve results on behalf of the client

Unstructured Data Storage


LOBCDER host (149.156.10.143)

LOBCDER service backend

Resource catalogue

WebDAV servlet

Resource factory

Storage driver

Storage driver (SWIFT)

SWIFT storage backend

Core component host (vph.cyfronet.pl) Data Manager

Portlet (VPH-‐Share

Master Interface component)

Atomic Service Instance (10.100.x.x) Service payload

(VPH-‐Share applicaGon component)

External host Generic WebDAV client

GUI-‐based access

Mounted on local FS (e.g. via davfs2)

•  VPH-‐Share federated data storage module (LOBCDER) enables data sharing in the context of VPH-‐Share applicaGons

•  The module is capable of interfacing various types of storage resources and supports SWIFT cloud storage (support for Amazon S3 is under development)

•  LOBCDER exposes a WebDAV interface and can be accessed by any DAV-‐compliant client. It can also be mounted as a component of the local client filesystem using any DAV-‐to-‐FS driver (such as davfs2).

EncrypGon keys

REST-‐interface

Master Interface component Ticket validaGon service

Auth service

Amazon S3 Storage backend

Platform by Numbers •  4 Data centers

– CYFRONET, Krakow – UoS, Sheffield – STH, Sheffield – UNV, Vienna

•  80+ Cloud Hosts •  100+ VMs baseline, 331 VMs Peak •  50TB+ Data Storage •  75+ Scientific Applications •  25+ Scientific Workflows •  €70k Public Cloud Burst Funds


Elephant in the Room

•  Security & Privacy •  Legislation & Ethics •  Training

•  Long Tail of Physicians and Care-takers

•  P4 Medicine Journey •  Predictive •  Preventative •  Personalised •  Participatory


<Thank You!>

42

Dr Susheel Varma <[email protected]> VPH-Share - Scientific Workflows Coordinator Department of Cardiovascular Science The Medical School, The University of Sheffield Beech Hill Road, Sheffield S10 2RX UK T: +44 (0)114 271 2863

#OIA4 04-‐Dec-‐13

•  @neurIST- Integrated Biomedical Informatics for the Management of Cerebral Aneurysms (http://www.aneurist.org)

•  IST project funded within the EU FP6 •  Duration: 2006-2010 •  Budget: 17M€ •  Participants: 28 institutions

–  Public and private, –  Industry, hospitals, academia, –  12 European countries

•  External collaborators: from USA, New Zealand, Japan)

•  @neurIST main objective: @neurIST will transform the management of cerebral aneurysms by providing new insights, personalized risk assessment, and methods for the design of improved medical devices and treatment protocols.

@neurIST Simulation Workflow

@neurIST Framework

VPH-‐Share

DICOM

Input: DICOM Output: 3D image DescripGon: Converts a DICOM image to VTK image

Volume Rendering

Input: 3D image Output: 3D image DescripGon: aneurysm and vessels VisualisaGon

Bounding Box

Input: 3D image Output: ROI DescripGon: volume selecGon

GAR Segmenta(on

Input: Image,ROI Output: surface mesh DescripGon: vessels and aneurysm extracGon

Mesh Edi(ng

Input: surface mesh Output: surface mesh DescripGon: clipping vessels, cleaning surface (cell removal, closing holes, smoothing…)

Skeletoniza(on

Input: surface mesh. Output: skeleton. DescripGon: necessary to set the boundary condiGons

Aneurysm isola(on

Input: surface mesh Output: surface mesh DescripGon: aneurysm isolaGon

Morphology Descriptors

Input: surface mesh Output: xml, vtk DescripGon: surface, depth… and ZMI calculaGon

Volumetric Mesh

Input: surface mesh Output: volumetric mesh DescripGon: creates a volumetric mesh of the selected geometry

Flow Simula(on

Input: volumetric mesh, ccl Output: wall shear stress map DescripGon: solves flow equaGons

Flow Simula(on post-‐processing

Input: wall shear stress Output: .csv file DescripGon: computes hemodynamic descriptors

CFD preprocessor

Input: xml, surface mesh Output: surface mesh, ccl DescripGon: Defines hemodynamic model

Input: surface, 1D model Output: xml, vtk DescripGon: boundary condiGons for CFD

Selec(ng Boundary Condi(ons

Neck Selec(on

Input: surface mesh Output: surface mesh DescripGon: aneurysm neck surface and dome selecGon

GIMIAS

@neuFuse

ANSYS (ICEM)

ANSYS (CFX)

Manual interacGon Common opera(ons


Hemodynamic analysis

Two Workflows from @neurIST

•  Morphological, hemodynamic and structural analyses have been linked to aneurysm genesis, growth and rupture.

•  Evidence indicating differences in morphology and flow between ruptured and unruptured aneurysms have been shown for reduced patient cohorts.

•  Structural wall mechanics has been used to justify the growth and remodelling happening at the aneurysm level.

Confidence in physical measures

+

images

+ BC, material

+ BC, material


Direct diagnos6c power

+

Morphological descriptors

Structural descriptors

Hemodynamic descriptors

Haemodynamic analysis

Structural analysis

PracGcally, morphological characterizaGons might currently have the highest predic(ve capabili(es with respect to the other analyses.

Morphological Workflow

The @neurIST morphological workflow specification in Taverna:

Implementation in VPH-Share

•  An automatic segmentation method based on Geodesic Active Regions (GAR) and an image standardization technique is used

•  The method: –  eliminates most of the dependency on the operator, and on

the specific imaging protocols and equipment used. –  is able to segment (extract the surface mesh) a region of

interest with a size of 2563 voxels in 17+4 min (avg+std dev) on a PC (Intel quad-core, 2.4 GHz, 4GB memory).

Hernandez, M. et al. 2007 Non-‐parametric geodesic acGve regions: method and evaluaGon for cerebral aneurysms segmentaGon in 3DRA and CTA. Med. Image Anal. 11, 224–241. Bogunovic, H. et al. 2011 Automated segmentaGon of cerebral vasculature with aneurysms in 3DRA and TOF MRA using geodesic acGve regions: an evaluaGon study. Med. Phys. 38, 210–222.

A surface mesh represenGng the vascular geometry is required to perform the @neurIST morphological and hemodynamic analyses

Medical image from imaging equipment

Surface mesh a<er segmenta6on

GAR Segmentation

•  The surface mesh obtained after the GAR segmentation needs to be manually manipulated by an operator to either remove or correct:

–  some of the artifacts not belonging to the cerebral vasculature –  those parts of the geometry not relevant for the subsequent

analyses (morphological or hemodynamic).

Surface mesh a<er segmenta6on

A surface mesh represenGng the vascular geometry is required to perform the @neurIST morphological and hemodynamic analyses

Kissing vessels Remove cells Close holes

O P

Surface mesh a<er correc6on and aneurysm isola6on

Mesh Editing

•  User is asked to manually delineate the neck •  Unfortunately, automatic methods are not an option

because there are: –  unacceptable differences in a large number of cases among

methods and manual selection of experts –  too complex vascular topologies where there is not even an

agreement among experts about where the aneurysm neck is

Several morphological measurements are based on the aneurysm sac, to idenGfy it, the aneurysm neck is required

Surface mesh a<er correc6on and aneurysm isola6on

Manual delinea6on

Manual aneurysm neck selec6on

vs Automat ic

Too large differences in performance and lack of consensus

Too complex vascular topologies

Neck DelineaGon

•  Among the wide variety of existing morphological descriptors, @neurIST chose to compute:

–  Basic size indices describing the aneurysm sac: aspect ratio, non-sphericity index, aneurysm volume and surface area.

–  Complex indices describing the sac and a portion of the surrounding vasculature: Zernike moment invariants (volume and surface-based).

Morphological descriptors of various complexity are automaGcally extracted and stored for their subsequent analysis

Ujiie, H. et al. 1999 Effects of size and shape (aspect raGo). Neurosurgery 45, 119–130. / Ma, B., Harbaugh, R. E. & Raghavan, M. L. 2004 Three-‐dimensional geometrical characterizaGon of cerebral aneurysms. Ann. Biomed. Eng. 32, 264–273. / Raghavan, M. L., Ma, B. & Harbaugh, R. E. 2005 QuanGfied aneurysm shape and rupture risk. J. Neurosurg. 102, 355–362. Pozo, J. M. et al. 2011 Efficient 3D Geometric and Zernike moments computaGon from unstructured surface meshes. IEEE Trans. Pagern Anal. Machine Intell. 33, 471–484.

Manual aneurysm neck selec6on

Complex indices (Zernike moment invariants)

Basic size indices describing aneurysm sac

depth

neck

@neurIST morphological descriptors

Morphological Descriptors

Medical image from imaging equipment

@neurIST morphological descriptors

Complex indices (Zernike moment invariants)

Basic size indices describing aneurysm sac

depth

neck

Morphological Analysis Workflow

@neurIST: Morphology Results

OpenStack in Action 4! Susheel Varma - VPH-Share: Patient-Centred Multi-scale Cloud-enabled...

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Transcript of OpenStack in Action 4! Susheel Varma - VPH-Share: Patient-Centred Multi-scale Cloud-enabled...