Glaucoma Simulation & Visualization

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Louisiana State University

www.cct.lsu.edu/IGERT

Glaucoma Simulation & Visualization

Presenter

Farid Harhad. IGERT Associate. Computer Science

Spring 2007 High School Workshop

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Overview Motivation What is Glaucoma? Anatomy of the Eye CFD Simulation of the Disease Eye Simulation Data Visualization of the Simulation Tutorial Highlights

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Motivation Investigating fundamental mechanisms of flow in

the eye helps us understand the leading causes of glaucoma

CFD simulation of glaucoma produces large amounts of data that can only be interpreted and analyzed using visualization

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Part 1:

Overview of the Disease

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What is Glaucoma? Glaucoma leads to blindness by damaging the

retinal cells[1]

Elevated pressure in the eye is a risk factor, but even people with normal pressure can lose vision[1]

World wide, second leading cause of blindness[1]

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Anatomy of the Eye (1/2) Light enters the eye by passing

through Cornea, anterior chamber, pupil, lens, vitreous body, retina

Optic nerve carries signal from retina to brain

High fluid pressure damages retinal nerve fibers and optic disc begins to hallow

[2]

[3]

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Anatomy of the Eye (2/2) Ciliary body consists of ciliary muscle and ciliary

processes Ciliary processes is a vascularized layer which

secretes a fluid called the aqueous humor (AH)

[2]

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Eye Fluid Drainage AH flows radially inward from ciliary body and drains in the

trabecular meshwork and Schlemm’s canals CFD simulation done for angle-closure glaucoma In angle-closure glaucoma, the iris deforms and blocks

normal flow

[5][5]

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Eye Vascular System

[4]

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Part 2:

CFD Simulation of the Disease

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CFD Simulation of Angle-Closure Glaucoma

1. Natural convection due to temperature difference between the ambient air (25 °C / 77 °F) and the interior of the eye (37 °C / 98.6 °F) leads to a buoyancy flow.

2. Apply the conservation of momentum law (fluid form of Newton’s law) to model the flow in the eye.

[2]

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Buoyancy Effect in the Eye

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CFD Simulation of Glaucoma

3. Mathematical equations of the physical model are numerically solved w/ computers: Material particle method (deformable iris) Immersed boundary (iris+fluid) Fluid solver (fluid)

4. Eye geometry information

was modeled using

ANSYS software and fed

into the numerical model

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Part 3:

Visual Analysis of the Simulation Results

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Eye Simulation Data Two types of datasets used:

iris geometry: consists of the vertices of the tessellated bottom surface of the iris

flow information: time-dependent velocities (u, v, w), P, & T at 69741 locations in the eye.

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Scalars Scalars

Physical quantities that are completely characterized by one number

Examples: mass of an object, temperature of an object, electrical potential, height …

2844 lbs 100 ºF 1.5 V

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Vectors Vector

Consists of a magnitude and direction

Vectors are often represented graphically by arrows

Examples: velocity of an object, gravity, magnetic field ...

Example: 112 mph

30 ~

60

μ T

esla

[7]

[8]

[6]

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Visualization Techniques Vector data: velocity distribution

LIC (Line Integral Convolution) basic idea

[9]

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Visualization Techniques Scalar data: pressure distribution w/ colormaps

Eg. often a color lookup table, is used to map a range of scalar data to a predefined color

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Visualization Process

T=0,T=1,…

T=1573

render geometry using polygons

render using LIC

render using a colormap

T=0,T=1,…

T=1573

Image Sequence(1574 timesteps)

Eye geometry

Vector data

Scalar data

CFDSimulation

DataVisualization

Movie Generation

(2) (3)(1)

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Visualization of The Results

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Recap Glaucoma is a group of diseases that leads to

blindness Common cause is when the aqueous humor does

not drain properly and pressure buildup damages the optic nerve

CFD computer model takes into account the buoyancy flow and conservation of momentum

We visualize the velocity of the flow in the eye using LIC (line integral convolution)

We visualize the pressure distribution in the eye using colormaps

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Tutorial Overview Two parts:

Part 1 (~10 min): familiarize yourself with visualization software

Part 2 (~25 min): load iris + flow data and visualize them

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Credits References:

1. http://en.wikipedia.org/wiki/Glaucoma

2. C. Ross et al. Ocular Biomechanics and Biotransport. Annu. Rev. Biomed. Eng. 2004.

3. Ian Albert. Anatomy of the Eye.

http://ian-albert.com/graphics/anatomy.php

4. Moore, Keith L. Moore. Essential Clinical Anatomy, 2nd Edition. LWW, 2002. 8.6.3

5. National Eye Institute. http://www.nei.nih.gov/photo/search/keyword.asp?keyword=glaucoma

6. http://en.wikipedia.org/wiki/Vector_%28spatial%29

7. http://www.calstatela.edu/faculty/acolvil/plates/magnetic_field.jpg

8. 3D Turbulent flow over a car. http://www.cmis.csiro.au/cfd/fem/car/index.htm

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Credits References (continued):

9. G. Erlebacher . Texture and Feature based Visualization. http://www-hagen.informatik.uni-kl.de/vis06-tutorial/materials/erlebacherVis06slides.pdf

Simulation Datasets: Dr. Anvar Gilmanov

Eye Flow Movie: Farid Harhad

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Thank you

Documents

Glaucoma Simulation & Visualization