Presentations

1.1 Introduction (Rob MacLeod, Dana Brooks)

1.2 Case Study I: Image based analysis of patients with atrial fibrillation (Rob MacLeod)

1.3 Demo I: Seg3D Demo and tutorial (Jess Tate)

Seg3D Software & Data

1.4 Lab I: Segmentation with Seg3D

1.5 Case Study II: Virtual Comparison of Deep Brain Stimulation Parameters (Tom Fogal)

1.6 Demo II: ImageVis3D/map3d demo and tutorial (Tom Fogal & Burak Erem)

ImageVis3D Software & Data
ImageVis3D Tutorial (pdf)
Getting Data Into ImageVis3D (pdf)
ImageVis3D Documentation (pdf)
map3d Software

1.7 Lab II: Visualization with ImageVis3D and map3D

1.8 Case Study III: Modeling of cardiac ischemia and arrhythmia (Rob MacLeod)

1.9 Demo III: BioMesh3D demo and tutorial (Derrell Swenson, Josh Levine)

SCIRun BioMesh3D Software & Data

1.10 Lab III: Mesh generation with BioMesh3D

1.11 Case Study IV: Simulation of defibrillation (Jess Tate)

1.12 Demo IV: SCIRun demo and tutorial (Jess Tate)

1.13 Lab IV: Simulation with SCIRun

CIBC Software Requirements

SCIRun

Windows: XP or better
OS X: 10.5, 10.6 (10.7 support is in progress)
Linux: SCIRun must be compiled from source and requires the following:
GCC 4 compiler
CMake 2.6 or greater
NVIDIA card and drivers

Installing platform-specific packages may be required.

SCIRun is known to compile on OpenSuSE 10 and 11, Ubuntu 9 and 10, and RHEL 5 (also CentOS and Fedora).

Seg3d

Windows minimum requirement: Windows XP, Windows Vista, or Windows 7, Strongly recommended 64bit operating system
Linux minimum requirement: Only for advanced users: need to build from source (build can take up to an hour), but should work on any Linux flavor

CPU: minimum Core Duo or higher, recommended i5 or i7
Memory: minimum 4Gb, recommended 8Gb or more
Graphics Driver: minimum OpenGL 2.0 or higher (Not available on older Intel embedded graphics cards)
Graphics memory: 128, recommended 256Mb or more

BioMesh3D

Python is required to run the BioMesh3D pipeline.
Multicore processor is strongly recommended.

Windows: Vista or 7
OS X: 10.5, 10.6
Linux: BioMesh3D must be compiled from source and requires the following:
GCC 4 compiler
CMake 2.6 or greater
NVIDIA card and drivers

Installing platform-specific packages may be required.

BioMesh3D comes packaged with SCIRun, which is known to compile on:

• OpenSuSE 10 and 11
• Ubuntu 9 and 10
• RHEL 5
• CentOS
• Fedora

ImageVis3d

Windows: Windows 7 or Windows Vista
Linux: Debian, Ubuntu, or Red Hat, with NVIDIA card and proprietary drivers.

Hardware, GPU: NVIDIA GeForce 9 series or better (i.e. GeForce 300M or later), or ATI/AMD Radeon HD 2400 series or better

map3d

Required: 1.5 GHz CPU, 1GB RAM, 10GB free disk space, 64MB video RAM
Recommended: Dual-core 2 GHz CPU, 2GB RAM, 10GB free disk space, 128MB video RAM
Operating systems: Windows XP, Vista, 7, Mac OSX 10.5 or greater

map3d can be built on many linux distributions (will require a C++ compiler and Qt SDK).

Extra Minisymposium at EMBS

Imaging and Computation in Clinical Electrocardiology

Investigators have been conducting research on the use of imaging and computation in electrocardiology for many years. However until fairly recently the impact of advances in this area on clinical practice has been minimal except in a few specialized areas. In contrast, recent research progress, combined with improvements in imaging and computational technology itself, have begun to result in many exciting possibilities for clinical application of research results. In particular the combination of imaging and computation is enabling dramatic expansion of the concept of "personalized medicine" beyond the world of genomics by enabling patient-specific modeling and simulation. This minisymposium will focus on both progress and challenges in three distinct clinical applications of imaging and computational research, from the points of view of three presenters who are each clinicians who are active in both clinical practice and research.

Presenter bios:

Ravi Ranjan, MD, PhD, is Assistant Professor of Medicine, University of Utah. He is a clinical cardiac electrophysiologist with a keen interest in understanding arrhythmia mechanisms and developing new therapies. His PhD research was on understanding ion channel physiology and cardiac excitation and propagation using experimental studies and mathematical modeling. He continued work on ion channel structure and function during his medical studies. Recent work focused on the importance of gaps in ablation lesion sets as a cause of poor outcome of ablation procedures. Currently, he is working on better understanding of atrial fibrillation in an animal model using MRI.

Petr Stovicek, MD, PhD, has been engaged in ECG research since 1986, He has worked on simultaneous cardiac polygraphy and body surface potential mapping and has published on pathologies, including comparative case-control studies and invasive measurements in patient with coronary artery disease and arrhythmias. After training at Dalhousie University and QEII Health Sciences Centre in Halifax, Canada, he opened a cardiac electrophysiology laboratory for Charles University Hospital (Department of Medicine II) in Prague, Czech Republic, where he introduced routine catheter ablations of arrhythmias. More recently he has been advancing clinical use of biophysical computer modellng and imaging (ECG lead transformation, inverse electrocardiography).

John Triedman, MD, is Professor of Pediatrics at Harvard Medical School and a senior cardiologist at Children's Hospital Boston, specializing in interventional cardiac electrophysiology. His research topics have included three-dimensional arrhythmia mapping, the pathogenesis of arrhythmias in congenital heart disease, the application of nonfluoroscopic navigation to catheter ablation, and modeling of defibrillating electrical fields in the human thorax.

Photos