Report Number: CS-TR-97-1586
Institution: Stanford University, Department of Computer Science
Title: Construction of a Three-dimensional Geometric Model for Segmentation and Visualization of Cervical Spine Images
Author: Pichumani, Ramani
Date: February 1997
Abstract: This report introduces a new technique for automatically extracting vertebral segments from three-dimensional computerized tomography (CT) and magnetic resonance (MR) images of the human cervical spine. An important motivation for this work is to provide accurate information for registration and for fusion of CT and MR images into a composite three-dimensional image. One of the major hurdles in performing image fusion is the difficulty of extracting and matching corresponding anatomical regions in an accurate, robust, and timely manner. The complementary properties of soft and bony tissues revealed in CT and MR imaging modalities makes it challenging to extract corresponding regions that can be correlated in an accurate and robust manner. Ambiguities in the images due to noise, distortion, limited resolution, and patient-specific structural variations also create additional challenges. Whereas fusion of CT and MR images of the cranium have already been performed, no one has yet developed an automated technique for fusing multimodality images of the spine. Unlike the head, which is relatively rigid, the spine is a complex, articulating object and is subject to structural deformation throughout the multimodal scanning process.