Visualization and Imaging

Our research in visualization has included investigations considering rendering, feature extraction and presentation, technique design, computational performance, and evaluations of technique effectiveness. We have considered visualization problems in many types of data, but have focused on volumetric, multidimensional, and large-scale data. Our computational performance interests include parallel feature extraction and data rendering using high performance computing. Our work in those areas has been supported by an NSF-funded Early Faculty Career Development (CAREER) Award and other funding sources. Previously, Dr. Newman also developed visualization tools for several medical applications under a post doctoral fellowship from the National Academy of Sciences at the National Institutes of Health and subsequently with funding from Cray Research. We also have interests in registration of volumetric datasets.

Isosurface Extraction
One major focus for us in visualization has been efficient, high quality isosurface extraction. We have studied and developed efficient MIMD parallel out-of-core approaches for large dataset isosurface extraction in multiprocessing environments. The approaches consider reduction in memory requirements and optimization of disk I/O, as well as load balancing across processors for the isosurfacing. Another focus in this area is the study and development of efficient multithreaded in-core and out-of-core isosurfacing approaches on new desktop computers with hyperthreading. The approaches consider reduction of memory requirements and total performance of isosurfacing.

Evaluation of Marching Isosurfacing Methods
The accuracy of the triangular mesh isosurface produced by marching isosurfacing methods is usually defined by the closeness of the produced mesh to the isosurface given by trilinear interpolation. One of our research efforts involved developing a new metric that evaluates the quantitative accuracy of marching isosurfacing methods. The new metric is an accurate estimate of spatial discrepancy between a produced mesh and the isosurface of trilinear interpolation. We also applied the metric to assess isosurfacing accuracy for certain scenarios.

Opacity Correction in Direct Volume Rendering (DVR)
Our research in this area has focused on investigating the correction of an artifact in over-sampled volume ray casting visualizations. We have developed new correction techniques for direct volume rendering cases where there are over-composited opacities. The new correction techniques are fast, generalized cell-by-cell approaches which introduce new opacity correction factors to avoid assuming dataset homogeneity. In addition, we have explored efficient approaches using commodity hardware to accelerate the opacity correction techniques. One class of approaches exploits a programmable graphics processing unit (GPU) in performing the arithmetic operations necessary to correct the opacities. Another class exploits cluster computing environments lacking programmable GPUs. A third class is a hybrid approach employs multi-threading using a dual core processor and a GPU.

Software Visualization
We have developed new approaches that aid understanding of object-oriented software through 3D visualization of software metrics. Our approaches allow extraction from the design phase of software development. The focus of the work is the metric extraction method and a new collection of glyphs for multi-dimensional metric visualization. Our approach automatically extracts the metrics for Unified Modeling Language (UML) class diagrams and generates 3D visualizations of these metrics for each class in the design.

Organ Extraction and Visualization
We have used volume growing, morphological operations, and locally adaptive histogramming to extract organs and other structures of interest from lower torso CT data. In our work, we addressed the renal complications of von Hippel Lindau (VHL) disease. Von Hippel Lindau patients tend to develop cysts and tumors in and on their kidneys. The cancers can be attacked surgically through removal of the diseased growths in and on the kidney. Due to stress on the renal system, the surgical intervention must be concluded subject to time constraints. One of the goals of our work was the accurate and timely detection and presentation of tumorous tissue. Through our three-dimensional visualizations, diagnosis and surgical planning were aided.

Brain Tissue Classification and Registrations
We have investigated classification of anatomical structures in brain CT and MR images. Our work is designed to develop strategies and techniques useful in frameless image-guided neurosurgery. Currently, it is difficult to use volumetric data, such as CT or MR, to guide surgery. One of the conventional approaches to neurosurgery involves the use of unwieldy stereotactic frames to allow registration of preoperative image data with intra-operative image data and surgical coordinates. Although less invasive approaches have been used at some medical centers, our aim was to aid in even less invasive approaches that exploit images in planning and guiding surgery. By classifying structures of interest in 3D datasets, the task of registering images of different modalities can be aided. Furthermore, the extraction and classification of structures of interest are a critical component for visualizations and renderings of the dataset for surgical planning and guidance.

We have developed methods for the extraction of the eyes, brain lateral ventricles, and brain longitudinal fissure. The ultimate goal of the feature extraction is to allow the registration of different modalities of MR datasets of the same individual (for example, registration of a T1-weighted dataset with MRA, T2-weighted, and proton density datasets).

Vector-Parallel Rendering
We have developed vector-parallel rendering techniques useful for medical visualization. Only a small number of research efforts to date have explored the possibility of using vector-parallel computation for visualization. We have developed both small-scale and full-scale vector-parallel realizations of the Marching Cubes isosurface extraction and applied this in tomographic images. We use Marching Cubes to generate a display of structures of interest, for example the spine, ribs, and several organs in mid- or lower-torso data. In application to kidney disease interventions, presenting a visualization of the spine and ribs helps orient a surgeon as he or she looks at the three-dimensional renderings to determine the positions of kidney cysts and tumors.

Plasmasphere Imaging, Visualization and Feature Detection
We have explored determining the volumetric density distribution of the plasma in the Earth’s plasmasphere. The plasmasphere is a region in the magnetosphere. The magnetosphere is a region around the Earth that is formed by the flow of plasma from the Sun and by the Earth’s magnetic field. The magnetosphere has several regions of varying plasma densities. Space physicists and scientists are interested to know the spatial distribution of the plasma in the plasmasphere in order to know more about the geomagnetic activities that occur in space. Hence this research work is an attempt to solve this space science problem.

IMAGE is a satellite that was launched by NASA in order to allow external investigation of the magnetosphere. The IMAGE has several instruments on board but our focus is on the Extreme Ultraviolet (EUV) imager, which takes global snapshots of the plasmasphere. The EUV instrument uses a photon imaging technique to image emissions from the Helium ions in the plasmasphere. The EUV instrument had 840x900 FOV and took one image of the plasmasphere every 10 minutes during its mission. Here is picture of the plasmasphere taken by the EUV instrument.

The focus of this research work in our lab can be classified into two main categories. One is determining the extent of the plasmapause boundary in the equatorial plane and the other is determining the volumetric plasma density distribution in the plasmasphere.

The link below access interactive software for identifying the plasmapause boundary and for determining a volumetric density distribution of the plasma from a series of EUV images.

Web-based Tool Suite for Plasmasphere Information Discovery
We have developed a suite of tools that enable discovery of terrestrial plasmasphere characteristics from NASA IMAGE Extreme Ultra Violet (EUV) images. Features supported by the tool suite include:

1. Magnetic Equatorial Plane Plasmapause Extraction
The first feature allows semi-automatic selection of the plasmapause boundary in an EUV image and maps the selected boundary to the geomagnetic equatorial plane. The plasmapause mapping feature is achieved via the Roelof and Skinner (2000) Edge Algorithm or Miminum L Algorithm.

2. Plasmasphere Reconstruction via Tomographic Imaging Technique
The second feature allows reconstructing the plasmasphere's plasma density distribution from a short sequence of EUV images. The plasma density reconstruction is achieved through tomographic technique that exploit physical constraints.

3. Plasmasphere Reconstruction via Latitude Variation Model Parameters Recovery
The third feature, plasmasphere reconstruction, recovers the plasmasphere's plasma density distribution through a robust fitting process that determines parameters of a variation of the Latitude Variation Model (LVM) (The proposed by Huang et. al. (2004). It is based on observation in IMAGE RPI data and requires determination of 5 parameters for each magnetic meridian plane.)

The Web-based Tool Suite can be accessed at:

We have also developed vector-parallel realizations of popular surface and volume ray-tracing techniques.

See the technical report