Graduation Year
2011
Document Type
Dissertation
Degree
Ph.D.
Degree Granting Department
Engineering Computer Science
Major Professor
Les A. Piegl, Ph.D.
Committee Member
Daniel C. Simkins, Ph.D.
Committee Member
Dmitry Goldgof, Ph.D.
Committee Member
Sudeep Sarkar, Ph.D.
Committee Member
Don Cameron, Ph.D.
Keywords
BioCAD, Tissue density variations, B-Spline curves, Anatomical contours, B-Spline surfaces
Abstract
Ongoing developments in the field of medical imaging modalities have pushed the frontiers of modern medicine and biomedical engineering, prompting the need for new applications to improve diagnosis, treatment and prevention of diseases.
Biomedical data visualization and modeling rely predominately on manual processing and utilization of voxel and facet based homogeneous models. Biological structures are naturally heterogeneous and in order to accurately design and biomimic biological structures, properties such as chemical composition, size and shape of biological constituents need to be incorporated in the computational biological models.
Our proposed approach involves generating a density point cloud based on the intensity variations in a medical image slice, to capture tissue density variations through point cloud densities. The density point cloud is ordered and approximated with a set of cross-sectional least-squares B-Spline curves, based on which a skinned B-Spline surface is generated. The aim of this method is to capture and accurately represent density variations within the medical image data with a lofted surface function.
The fitted B-Spline surface is sampled at uniformly distributed parameters, and our preliminary results indicate that the bio-CAD model preserves the density variations of the original image based point cloud. The resultant surface can thus be visualized by mapping the density in the parametric domain into color in pixel domain. The B-Spline function produced from each image slice can be used for medical visualization and heterogeneous tissue modeling. The process can be repeated for each slice in the medical dataset to produce heterogeneous B-Spline volumes.
The emphasis of this research is placed on accuracy and shape fidelity needed for medical operations.
Scholar Commons Citation
Grove, Olya, "Heterogeneous Modeling of Medical Image Data Using B-Spline Functions" (2011). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/3130
Included in
American Studies Commons, Bioimaging and Biomedical Optics Commons, Computer Sciences Commons
