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West Virginia University

Three-dimensional image reconstruction of skeletal tissue from computed tomography

Abstract

dc:description.abstract

Edge Detection Techniques play a very important role in medical imaging. Pre-operative diagnosis of diseases such as cancer, tumors, bone fractures etc. depend on edge detection techniques to identify the malignant growths. In orthopedics, edge detection techniques are used in the reconstruction of the skeletal system from modalities such as MRI (magnetic resonance imaging) and CT (computed tomography).;In this thesis, we develop a simple process for the three dimensional image reconstruction of the human knee, starting from computed tomography scans. Designing a digital image processing technique which successfully separates the bone from the surrounding flesh and muscle tissue is the main focus of the thesis. We use edge detection procedures to extract the edge of the bone. After the bone edge is determined, we proceed to extract the coordinates of the bone boundary. These coordinates are plotted in 3 dimensional space providing the 3D model of the human skeletal leg.;The 3D reconstruction method developed in this thesis is applicable to all skeletal tissue but is illustrated using the CT images of the human leg.

Degree

thesis:*
Name thesis:degree_name
MS
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Lane Department of Computer Science and Electrical Engineering
Year dc:date.available
2000

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Jayashekar, Sundareswar Bangalore
Contributors dc:contributor
  • Bojan Cukic.

Subjects

dc:subject × 4

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:researchrepository.wvu.edu:etd-2079

Chain of custody

source
Harvested from
West Virginia University
Base URL
researchrepository.wvu.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Jayashekar, Sundareswar Bangalore. Three-dimensional image reconstruction of skeletal tissue from computed tomography. Thesis thesis, 2000. https://doi.org/10.33915/etd.1076