Medical image segmentation is an increasingly important component in virtual pathology, diagnostic imaging and computer-assisted surgery. Better hard\vare for image acquisition and a variety of advanced visualisation methods have paved the way for the development of computer based tools for medical image analysis and interpretation. The routine use of medical imaging scans of multiple modalities has been growing over the last decades and data sets such as the Visible Human Project have introduced a new modality in the form of colour cryo section data. These developments have given rise to an increasing need for better automatic and semiautomatic segmentation methods. The work presented in this thesis concerns the development of a new framework for robust semi-automatic segmentation of medical imaging data of multiple modalities. Following the specification of a set of conceptual and technical requirements, the framework known as ACSR (Adaptable ClassSpecific Representation) is developed in the first case for 2D colour cryo section segmentation. This is achieved through the development of a novel algorithm for adaptable class-specific sampling of point neighbourhoods, known as the PGA (Path Growing Algorithm), combined with Learning Vector Quantization. The framework is extended to accommodate 3D volume segmentation of cryo section data and subsequently segmentation of single and multi-channel greyscale MRl data. For the latter the issues of inhomogeneity and noise are specifically addressed. Evaluation is based on comparison with previously published results on standard simulated and real data sets, using visual presentation, ground truth comparison and human observer experiments. ACSR provides the user with a simple and intuitive visual initialisation process followed by a fully automatic segmentation. Results on both cryo section and MRI data compare favourably to existing methods, demonstrating robustness both to common artefacts and multiple user initialisations. Further developments into specific clinical applications are discussed in the future work section.

Thesis (M.A.) -- University of Texas Southwestern Medical Center at Dallas, 2005. / Vita. Bibliography: 159.

Computational modeling offers better insight into a wide range of bioelectrical and biomechanical problems with improved tools for the design of medical devices and the diagnosis of pathologies. Electromagnetic modeling at low and high frequencies is particularly necessary. Modeling electromagnetic, structural, thermal, and acoustic response of the human body to different internal and external stimuli is limited by the availability of numerically efficient computational human models. This study describes the development to date of a computational full-body human model - Visible Human Project (VHP) - Female Model. Its unique feature is full compatibility both with MATLAB and specialized FEM computational software packages such as ANSYS HFSS/Maxwell 3D. This study also describes progress made to date in using the newly developed tools for segmentation. A visualization tool is implemented within MATLAB and is based on customized version of the constrained 2D Delaunay triangulation method for intersecting objects. This thesis applies a VHP - Female Model to a specific application, transcranial Direct Current Stimulation (tDCS). Transcranial Direct Current Stimulation has been beneficial in the stimulation of cortical activity and treatment of neurological disorders in humans. The placement of electrodes, which is cephalic versus extracephalic montages, is studied for optimal targeting of currents for a given functional area. Given the difficulty of obtaining in vivo measurements of current density, modeling of conventional and alternative electrode montages via the FEM has been utilized to provide insight into the tDCS montage performance. An insight into future work and potential areas of research, such as study of bone quality have been presented too.

The use of virtual reality (VR) for visualization can revolutionize medical training by simulating real world medical training procedures through intuitive and engaging user interface. Existing virtual reality based visualization systems for human anatomy are based on 3D surface and volumetric models and simulative systems based on model libraries. The visual impact as well as facilitation for learning are inadequate in such systems. This thesis research is aimed at eliminating such inadequacies by developing a non-immersive virtual reality system framework for storage, access and navigation of real human cadaveric data. Based on this framework, a real time software system called virtual cadaver navigation system (VCNS) is developed, that can be used as an aid for teaching human anatomy. The hardware components of the system include, a mannequin, an examination probe similar to a medical ultrasound probe, and a personal computer. The examination probe is moved over the mannequin to obtain the virtual tomographic slice from the real cadaveric3-D volume data. A 3-D binary space partitioning tree structure is defined to organize the entire volumetric data, by subdividing it into small blocks of predefined size, called as bricks that are assigned a unique address for identification. As the examination probe is moved over the mannequin, the set of bricks intersecting the corresponding tomographic slice are determined by traversing the tree structure, and only, the selected bricks are accessed from the main memory and brought into the texture memory on the graphics accelerator card for visualization. The texture memory in the graphics card and the main memory are divided into slots of size, that is a multiple of the brick size, and a tagging scheme that relates the brick addresses, texture memory slots, and the main memory blocks is developed. Based on spatial, temporal and sequential locality of reference, only the currently required bricks as well as some of the neighboring bricks are loaded from the main memory into the texture memory, in order to maintain the highest frame rates required forreal time visualization. The above framework consisting of the data organization and the access mechanism are critical in terms of achieving the interactive frame rates required for real-time visualization. The input data to the system consists of non-segmented voxel data, and the data segmented and labelled based on tissue classification. The software system includes a labeling tool, in order to display the specific tissue information at the the location of the mouse cursor. This facility is useful in both teaching anatomy and self learning. Thus, the proposed VCNS system supports efficient navigation through the human body for learning anatomy and provides the knowledge of spatial locations and the interrelationship among the various organs of the body. A prototype software system has been developed, which is capable of achieving a throughput of 30 frames per second and has been tested with a 18-Gigabyte human cadaveric data obtained from the National Library of Medicine, on a personal computer with 64 Megabytes of texture memory and 512 Megabytes of main memory.

This thesis contends that technologically-derived resurrections of human bodies and bodily fragments can be viewed as indicative of a 'post-biological' ontology. Drawing from examples in which human bodies are resurrected, both figuratively and actually, this thesis puts forward the term 'post-biological subject' as an ideological framework for conceptualising the reconfiguration of human ontology that results from various medical technologies that 'resurrect' the human body. In this instance, the term 'postbiological', borrowed from Hans Moravec who uses it denote a future in which human being is radically disembodied and resurrected within a digital realm, is used somewhat ironically: where Moravec imagines an afterlife in which the body is discarded as so much 'meat', the post-biological afterlife of the body in this thesis centres around a form of corporeal resurrection. Corpses, living organs and excreta may all be resurrected, some of them in digital format, yet this kind of resurrection departs radically from the disembodied spiritual bliss imagined in many conceptualisations of resurrection. The post-biological subject resists ontological delineation and problematises boundaries defining self and other, living and dead, and human and nonhuman and is fraught with a number of cultural anxieties about its unique ontological status. These concerns are analysed in the context of a number of phenomena, including melancholy, horror, monstrosity and the uncanny, all of which similarly indicate an anxious fixation with human ontology. The purpose of discussing post-biological bodies in relation to phenomena such as melancholy or the uncanny is not to reinstate as ideological frameworks the psychoanalytic models from which these concepts are derived, but rather to use them as starting points for more complex analyses of postbiological ontology. The first and second chapters of this thesis discuss instances in which the human body is posthumously modified, drawing on Gunther von Hagens's Body Worlds exhibition and the Visible Human Project. The Body Worlds plastinates are situated in a liminal and ambiguous ontological space between life and death, and it is argued that their extraordinary ontological status evokes a form of imagined melancholy, wherein the longed-for and lost melancholic object is a complete process of death. In the case of the Visible Human Project, it is argued that the gruesome and highly technologised process of creating the Visible Male, wherein the corpse is effectively dehumanised and iv rendered geometric, evokes the trope of horror, while at the same time being fraught with a nostalgic longing for a pre-technological, anatomically 'authentic' body. The third and fourth chapters of this thesis discuss instances in which the living human body is reconfigured, focusing on immortal cell lines and organ transplantation, and on medical imaging technologies such as computed tomography and magnetic resonance imaging. In the third chapter it is argued that organ transplantation and the creation of immortal cell lines give rise to profound anxieties about ontological contamination through their capacity to render permeable the imagined boundaries defining self, and in this way invoke the monstrous. The fourth chapter interrogates the representation of medical imaging in Don DeLillo?s novel White Noise, arguing that the medical representation of the body functions as a form of double, a digital doppelganger that elicits an uncanny anxiety through its capacity to presage death.