Doctor of Philosophy, The Ohio State University, 2011, Biophysics

The current state of biological science is such that many sources of data are simply too large to be analyzed by hand. Furthermore, given the amazing breadth of investigation into the natural world, the potential for serious investigation from just mining heterogenous data sets is too rich to ignore. These two factors combined with the amount of computational power currently available make for ideal conditions from the perspective of visual analytics. Here we describe three computational projects focused on the visualization and analysis of data within the fields of microbial pathogenesis, cell biology, and molecular conformational dynamics. ProkaryMetrics is a new software package providing 3D reconstruction of fluorescent micrographs as well as various visual and statistical tools for analysis of bacterial biofilms. The software FIND is a new platform for promoting computational analysis and enhanced visualization of multicolor flow cytometry data. FIND provides users with user-friendly, cross-platform analysis software, while simultaneously providing algorithm designers a target for implementation. Finally, the Moflow project represents a new visual representation of atomic flow within molecules during conformational changes over time in a more intuitive sense than was previously possible.

Committee: William Ray PhD (Committee Chair); Sheryl Justice PhD (Advisor); Shen Han-Wei PhD (Committee Member); Luis Actis PhD (Committee Member); Charles Daniels PhD (Committee Member) Subjects: Bioinformatics; Biophysics; Computer Science

Doctor of Philosophy, The Ohio State University, 2011, Computer Science and Engineering

Computer surgical simulation has a great deal of potential in medical education and testing. However, there are numerous problems in integrating simulation software technology into a medical curriculum. Review and analysis of the data from the simulation is important to evaluate and assist students. A combination of realistic rendering for good translation of skills to the operating room and illustrative rendering to aid novices can help the simulation system target a wide range of students. In the context of an ongoing project to develop and improve a temporal bone surgical simulator, this document describes algorithms that address these issues and provides solutions to them. In collaboration with expert surgeons, we have met some of the technological challenges that limit surgical simulation. Storage and playback of the interactions that users have with the simulation system is achieved via a snapshot technique using forward differences for efficient compression. A technique for realistic rendering of fluid and wet surfaces in a virtual surgical environment using modern graphics hardware is explained. Using a modified distance field technique, we show how to display context around important anatomical structures in segmented datasets. A method of automatic scoring of the users of the simulator is detailed. This method involves partitioning the volume based on proximity to critical structures and then using the Earth Mover's Distance to compare the content of those partitions. Distance fields are also employed for shape analysis techniques to extract features that are used in a visualization system. This system allows expert surgeons to examine and compare the virtual mastoidectomies perfomed by residents during training.

Committee: Han-Wei Shen PhD (Committee Chair); Roger Crawfis PhD (Committee Member); Raghu Machiraju PhD (Committee Member) Subjects: Computer Science; Medical Imaging

Master of Arts, The Ohio State University, 2010, EDU Teaching and Learning

In this study, I am taking what Cobb and Yackel (1996) called an “emergent” perspective, which is a blend of psychological and socio-cultural perspectives from the constructivist paradigm, to investigate how fifth graders construct and modify their mental models and processes for understanding volume measurement in terms of cube-package enumeration problems. In particular, this study is an extension of the Battista's 1999 study, in which he investigated how fifth grade students predicted and enumerated the number of cubes in a rectangular box in an inquiry-based classroom. I describe the work and reasoning of two pairs of fifth grade boys as they predicted the number of cube-packages that fit into graphically represented boxes in an inquiry-based classroom. This study extends on the essential mental processes that previous research has already defined for cube enumeration problems (Battista, 1999; Battista & Clements, 1996), and describes three additional essential mental processes (locating, positioning, and orienting) that students need to do for cube-package enumeration problems. The results of this study indicate that there are three types of mental models used by the students when dealing with package problems: layer based, non-layer composite-unit based, and non-composite-unit based. Finally, I describe some of the cognitive obstacles and errors that occur when students attempt to solve cube-package problems.

Committee: Michael Battista PhD (Advisor); Douglas Owens PhD (Committee Member) Subjects: Education; Elementary Education; Mathematics Education

Doctor of Philosophy, The Ohio State University, 2008, Computer Science and Engineering

Graphics hardware based volume visualization techniques have been the active research topic over the last decade. With the more powerful computation ability, the availability of large texture memory, and the high programmability, modern graphics hardware has been playing a more and more important role in volume visualization.In the first part of the thesis, we focus on the graphics hardware acceleration techniques. Particularly, we develop a fast X-Ray volume rendering technique using point-convolution. An X-ray image is generated by convolving the voxel projection in the rendering buffer with a reconstruction kernel. Our technique allows users to interactively view large datasets at their original resolutions on standard PC hardware. Later, an acceleration technique for slice based volume rendering (SBVR) is examined. By means of the early z-culling feature from the modern graphics hardware, we can properly set up the z-buffer from isosurfaces to gain significant improvement in rendering speed for SBVR. The high programmability of the graphics processing unit (GPU) incurs a great deal of research work on exploring this advanced graphics hardware feature. In the second part of the thesis, we first revisit the texture splat for flow visualization. We develop a texture splat vertex shader to achieve fast animated flow visualization. Furthermore, we develop a new rendering shader of the implicit flow. By careful tracking and encoding of the advection parameters into a three-dimensional texture, we achieve high appearance control and flow representation in real time rendering. Finally, we present an indirect shader synthesizer to combine different shader rendering effects to create a highly informative image to visualize the investigating data. One or more different shaders are associated with the voxels or geometries. The shader is resolved at run time to be selected for rendering. Our indirect shader synthesizer provides a novel method to control the appearance of the (open full item for complete abstract)

Committee: Roger Crawfis PhD (Advisor); Raghu Machiraju PhD (Committee Member); Han-Wei Shen PhD (Committee Member) Subjects: Computer Science

Doctor of Philosophy, The Ohio State University, 2006, Computer and Information Science

The sizes of large data sets, ranging from gigabytes to terabytes, pose a formidable challenge to conventional volume visualization algorithms. Multiresolution rendering proves to be a viable solution to this challenge by reducing the actual amount of data sent to the rendering pipeline. However, previous multiresolution rendering algorithms are inherently sequential, which hinders their applications in parallel environments, such as PC clusters with increasing availability. Moreover, most of the existing algorithms for large volume visualization use data-based metrics for level-of-detail selection and provide very limited user interaction and control. There is lack of techniques and tools for more effective level-of-detail selection and rendering. I present a multiresolutional approach for representing, managing, selecting, and rendering large-scale three-dimensional steady and time-varying data sets. A multiresolution volume rendering algorithm is proposed to visualize large data sets in parallel environments that ensures a well-balanced workload. A comprehensive image-based quality metric is introduced for quality-driven interactive level-of-detail selection and rendering of large data sets. Furthermore, a new visual navigation interface is presented for the user to examine, compare, and validate different level-of-detail selection algorithms. Future research focuses on transfer function design for large-scale time-varying data, which includes spatio-temporal data reduction, transfer function design, and user interface support for space-time data exploration.

Committee: Han-Wei Shen (Advisor) Subjects: Computer Science

Doctor of Philosophy, The Ohio State University, 2006, Computer and Information Science

Although many advances have been achieved within the visualization community in the last decade, many challenging problems are still open in volume rendering. In this dissertation, we mainly study three challenging topics in advanced volume rendering on shadows, flows, and high-dimensional rendering. Shadows are essential to realistic and informative scenes. In volume rendering, the shadow calculation is difficult because the light intensity is attenuated as the light traverses the volume. We investigate a new shadow algorithm that properly determines the light attenuation and generates more accurate volumetric shadows with low storage requirements by using 2D shadow buffers. We have extended our shadow algorithm to deal with extended light sources and generate volumetric soft shadows with an analytic method and using a convolution technique. This shadow and soft shadow algorithm also has been applied to mixed scenes of volumetric and polygonal objects. Multiple light scattering is also modeled in our volumetric lighting model. Interval volume algorithm is a region-of-interest extraction algorithm for steady and time-varying three-dimensional structured and unstructured grids. We present several new rendering operations to provide effective visualizations of the 3D scalar field. This technique has been extended to four dimensions to extract time-varying interval volumes. The time-varying interval volumes are rendered directly, from 4-simplices to image space. We propose a high-dimensional rendering algorithm and solve this technical challenge. In this way, we can visualize the integrated interval volumes across time steps and see how interval volumes change over time in a single view. Three-dimensional flow visualization is a challenging topic. We propose an implicit flow field method to visualize 3D flow fields. An implicit flow field is first extracted using an advection operator on the flow, with a set of flow-related attributes stored. Two techniques are then em (open full item for complete abstract)

Committee: Roger Crawfis (Advisor) Subjects: Computer Science

Doctor of Philosophy, The Ohio State University, 2005, Computer and Information Science

Much progress has been made in the field of visualization over the past few years; but in many situations, it is still possible that the available visualization resources are overwhelmed by the amount of input data. The bottleneck may be the available computational power, storage capacity or available manpower, or a combination of these. In such situations, it is necessary to adapt the algorithms so that they can be run efficiently with less computation, with less space requirements, and with less time and effort from the human user. In this thesis, we present three algorithms that work towards reducing the resource constraints while maintaining the integrity of the visualizations. They are bound by a common underlying theme that all data elements are not equal in the particular visualization context – some are more important than others. We use certain data properties to create “importance“ measures for the data. These measures allow us to control the distribution of resources – computational, storage or human – to different portions of the data. We present a space efficient algorithm for speeding up isosurface extraction. Even though there exist algorithms that can achieve optimal search performance to identify isosurface cells, they prove impractical for large datasets due to a high storage overhead. With the dual goals of achieving fast isosurface extraction and simultaneously reducing the space requirement, we introduce an algorithm based on transform coding. We present a view selection method using a viewpoint goodness measure based on the formulation of entropy from information theory. It can be used as a guide which suggests good viewpoints for further exploration. We generate a view space partitioning, and select one representative view for each partition. Together, this set of views encapsulates the most important and distinct views of the data. We present an interactive global visualization technique for dense vector fields using levels of detail. It comb (open full item for complete abstract)

Committee: Han-Wei Shen (Advisor) Subjects: Computer Science