Human Body in a 3-D, Immersive,

Applied Anatomical Diagnostic
Framework for Visualizing the
Human Body in a 3
-
D, Immersive,
Navigable and Interactive VR
Environment

May 4, 2012

Steven
Beaudoin
, BS

George D.
Lecakes

Jr., MS

Tony
Aita
, BS

Lawrence Weisberg, MD

Michael Goldberg, MD

Vijay Rajput, MD

Shreekanth

Mandayam
, PhD

Contributing Authors

Steven


Beaudoin

George
Lecakes
, MS

Shreekanth

Mandayam
, PhD

Michael
Goldberg, MD

Vijay


Rajput
, MD

Lawrence
Weisberg, MD

Overview

•
Background

•
Objectives

•
Approach

•
Results

•
Future Goals

•
Conclusions

•
Acknowledgements

-
US Department of Education, 2010


“ To consider integration of 21
st

century competencies, expertise, such
as critical thinking, complex problem
solving,
collaboration, multimedia
communication,
and technological
competencies demonstrated by
professional disciplines”

Cooper Medical School

CAVE® at Medical School

•
Basic anatomy


•
Clinical correlation


•
Systems based practice educational tool


•
Simulation scenarios (simulated patients /
conditions)


Background

The Rowan University CAVE®

Background

The Rowan University CAVE®

•
7.5'h x 10'w x 10'd tracked virtual environment
covering 3
-
walls and a floor

•
4
-

active stereo DLP projectors, 3,000 ANSI lumens,
1400x1050 resolution, with short
-
throw zoom lens

•
CAVE® structure fabricated with extruded &
powdercoated

80/20 aluminum,

•
8
-
camera
WorldViz

IR position tracking system

•
CrystalEyes
® active shutter glasses

•
6
-

PC computer cluster

•
WorldViz

Vizard, Autodesk 3D Studio Max / Maya

Objectives

•
Provide intuitive
correlation of clinical
information


•
Utilize a CAVE® virtual reality (VR) environment to
enhance viewing of data sets


•
Ask “what
if?” questions and simulate multiple scenarios
for
pathological/anatomical diagnosis


•
Utilize multiple diagnostic imaging procedures for
prognostic capability


Approach


Data preparation


•
CT
-

dataset of volunteer torso from the skull to the pelvis


•
Consisted of 909 images at 1mm slices


•
Provided in DICOM data format with each image having a different window
center and window width

Data
Preparation

Data
Preprocessing

Data
Visualization

Real
-
Time
Processing

Approach


Data preprocessing


•
Utilize image processing tool (MATLAB) to convert images into a standard window center
and window width


•
Converted the various ranges into standard grayscale range (0
-
255)

•
0
–

Black

•
255
–

White


•
Export images to CAVE compatible file format (
tga,png,jpeg
)


Data
Preparation

Data
Preprocessing

Data
Visualization

Real
-
Time
Processing

Approach

Data
Preparation

Data
Preprocessing

Data
Visualization

Real
-
Time
Processing

Raw data

Processed Data

Approach


Data Visualization


•
Load images (textures) sequentially


•

Textures are applied to a series of
evenly spaced polygonal planes


•
Each plane represents one cross
-
sectional slice of patient data


•
Images are given transparency


•
Images are rendered back to front

Data
Preparation

Data
Preprocessing

Data
Visualization

Real
-
Time
Processing

Approach


Pixel Values


•
Values from a CT scan
represent different densities


•
Radiolucent regions are low
density
–

air


•
Radiodense

regions are
higher density
–

bone

Data
Preparation

Data
Preprocessing

Data
Visualization

Real
-
Time
Processing

Approach


Data Manipulation and Interface


1.
Grayscale histogram
–

Cull pixel values from the histogram
using a range slider.


2.
Pseudo
-
color histogram
–

Cull pixel values and color the
ranges with red, green, or blue ranges.


3.
Clip Plane Mode
–

Clip the polygonal planes with an
OpenGL clipping plane in any orientation.


Xbox 360® Controller
–

All functionality mapped to buttons

Data
Preparation

Data
Preprocessing

Data
Visualization

Real
-
Time
Processing

Educational / Future Medical Applications

•
Learn anatomy / clinically applied anatomy in
3D virtual reality


•
Anatomic pathology and radiological
integration


•
Correlation of surface and organ anatomy for
surgical procedure


•
Application of 3D virtual reality to understand
system based practice
–

e.g. Assess Home
environment for safety for geriatric patient


Other uses of CAVE®

Work In Progress



Fuse multiple image data sets (MRI, CT, PET) to
distinguish redundant and complementary
information for clinically applied anatomical
education

Work In Progress

Acknowledgments


We gratefully acknowledge the assistance of:


Dr. H. Warren Goldman, MD, PhD

Professor and Chair of Neurosurgery

Cooper Hospital, Camden, NJ


Mr. Anthony
Aita

Neurosurgery Department

Cooper Hospital, Camden, NJ


Approach

Approach