Overview | Current Projects | Publications | Theses | Sponsors | MS/Phd Theses Topics |
A variety of graphics and visualization tools such as OpenGL, Visualization
Toolkit (VTK), Insight Registration and Segmentation Toolkit (ITK),
as well as scripting languages such as Tcl, Python are used in
research projects, largely on Unix (Linux) platforms.
[MOVIE-Training Exercise(MPEG)]
[MediaReport(WSOC TV)-TrainingExercise(Quicktime)(72 MBytes)]
[MediaReport(WSOC TV)-TrainingExercise(Quicktime)(162 MBytes)]
[MOVIE-Evac Table Top Exercise(Quicktime)]
Mammography is currently regarded as the most effective and widely used
method for early detection of breast cancer, but recently its
lower sensitivity in certain high risk cases has been less than desired.
The use of Dynamic Contrast Enhanced MRI (DCE-MRI) has gained
considerable attention in recent years, especially for high risk
cases, for smaller multi-focal lesions, or very sparsely distributed
lesions. This project is focused on constructing interactive visualization
tools to identify, process, visualize and quantify lesions from
DCE-MRI volumes. Our approach segments the time varying volume data
in near-real time and employs 3D texture mapped volume rendering in
a highly interactive environment.
(Joint Work with Dr. John Brockway, Novant HealthCare, Charlotte, NC).
Sample 3D Reconstructions:
Current Research Projects
The project focuses on the problem of plotting the position of an
endoscopic camera (during a colonoscopy procedure) on the correspond-
ing pre-operative CT scan of the patient. Given that virtual colonoscopy
is emerging as an alternate screening tool, automatic tracking
techniques can benefit colonoscopy procedures by presenting both
modalities simultaneously and possibly reduce errors.
[Full Paper(PDF)]
This project involves the construction of an infrastructure for visual
learning system. The system provides an interactive interface for
building teaching modules, thus enabling instructors across disciplines
easy access and use of the system for building visually rich
content. The initial version of the system has been developed to
handle basic concepts in computer science, specifically algorithms
and data structures.
[Full Paper(PDF)]
[MOVIE-EERC System(Quicktime)]
[Full Paper(PDF)]
Past Research Projects
Interactive Detection, Visualization and Quantification
of Breast Lesions from DCE-MRI Volumes
Modeling and Visualization of DNA Microarray Data
Whole genome expression profiling using DNA microarrays represent a major advance in genome-wide functional analysis, for understanding gene function, gene interactions, metabolic pathways, signal transduction pathways, and effects of environmental factors. The central challenge is to rapidly and efficiently extract useful information and discover knowledge from these large data sets, which can improve our comprehension of human disease, and facilitate drug development. This project employs information visualization techniques to view and interact with the output of modeling techniques (such as Graphical Gaussian, Loglinear, Causal) applied to DNA Microarray data. The output is in the form of multivariate relationships. The complexity and nature of these relationships motivates the use of visualization techniques and is expected to lead to new knowledge of biological pathways.
This project involves the reconstruction and visualization of 3D Intravascular Ultrasound image sequences, study and characterization of cholesterol induced blockages (atherosclerotic plaques). In the first part of this study, two vessels (bovine and dog arteries) were imaged, in vitro, reconstructed in 3D and visualized. The reconstructions were validated both qualitatively and quantitatively and an error within 10% was achieved. Future work on this project will involve 3D system development and in-vivo studies (Sponsored by the American Heart Association. Joint work with Heineman Medical Research Laboratory, Carolinas Medical Center).
This project explores information
visualization schemes to interactively control,
drive and analyze simulations of adaptive resource management
protocols in mobile networks. In particular, the research will
use interactive steering to optimize multi-layer
adaptive protocols, via visualization interactions of appropriate
simulation variables (system monitoring metrics, metric parameters
and simulation system parameters)(Joint work with Dr. Teresa Dahlberg,
UNC Charlotte)
(Sponsor: National Science Foundation).
This project explores new techniques for
active contour models, popularly known as snakes,
by combining active segmentation
models with constrained implicit surface models
recently reintroduced under the name of variational implicit
surfaces. Ongoing work explores algorithm for efficient representation
of large medical models using variational implicits, computationally
more efficient basis functions, etc.
Example CT Reconstruction of a Tooth Using Implicit Snakes
Example Intravascular Ultrasound Reconstruction of a Blood Vessel
This project will provide a visual display of output data
and a rapid data-analysis package for simulations of spinal cord
circuits. The particular circuits of interest are those
controlling hindlimb muscles of a mammal, such as cat or human.
The data, consisting of time and identity(location) of active
cells in each population at each millisecond, are generated by
a large-scale computational model of a pair of motoneuronal
populations interconnected with ten or more interneuronal
populations. The two motoneuronal populations represent the
output to a pair of antagonistic (i.e., flexor-extensor)
muscles. Neuron electrical properties and connection patterns
are reasonable representations from the literature. The network
contains on the order of 2500 cells and 650,000 connections.
Inputs to the circuit consist of a number of fiber populations
representing sensory inputs and descending control from the
brain.
The visualization package will provide display of time
and location of active cells for all the populations, as well
as computing elementary cell and population performance
statistics. An important goal of the project is to combine the
simulations (experiments) and the data analysis (which will also be,
for the most part, graphical) to function in a single computing
environment. This is expected to drastically reduce the turn-around time
from experiment to analyzed data (eight fold reduction is estimated).
(In collaboration with Dr.David Bashor, Dept. of Biology) The sample animation below shows the activity of three state variables,
membrane potential (green), threshold potential (yellow) and
spike production (grey) over a time interval of 66 milliseconds.
The six populations on the left and the the lone population on the upper
right corner are fiber populations, while the remaining 15 are cell
populations. Each population represents 100 cells (neurons), arranged
within a 10 by 10 grid.
(In Collaboration with Dr. David Bashor,
Dept. of Biology, UNC Charlotte)
The goal of this project is to convert medical images (CT, MRI, etc) from
a discrete lattice of values into a partitioning tree representation that
is piece-wise continuous. This enables many viewing and spatial operations
to be performed with great ease and at interactive rates. Applications
include interactive visualization of medical data, surgery
planning/rehearsal/training and prostheses design
(Joint work with Dr. Bruce Naylor, University of Texas at Austin).
Synthetic Image: Lenna Medical Image : MRI Brain Images
MS/Phd Theses Topics
Research Sponsors
Last update: K.R. Subramanian (krs@uncc.edu), March 7, 2004