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Cone-beam helical CT virtual endosco...

Carvalho, Bruno Motta de.

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Cone-beam helical CT virtual endoscopy: Reconstruction, segmentation and automatic navigation.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Cone-beam helical CT virtual endoscopy: Reconstruction, segmentation and automatic navigation./
Author:	Carvalho, Bruno Motta de.
Description:	182 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5030.
Contained By:	Dissertation Abstracts International64-10B.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3109160
ISBN:	0496567039

Cone-beam helical CT virtual endoscopy: Reconstruction, segmentation and automatic navigation.
Carvalho, Bruno Motta de.

Cone-beam helical CT virtual endoscopy: Reconstruction, segmentation and automatic navigation. - 182 p.

Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5030.

Thesis (Ph.D.)--University of Pennsylvania, 2003.

Virtual Endoscopy (VE) is a technique in which three-dimensional (3D) data, acquired by an imaging technique such as Computerized Tomography (CT) or Magnetic Resonance Imaging (MRI), is segmented and presented in an animation so as to mimic an endoscopic examination, i.e., as if a camera were introduced into an anatomical structure. It has been shown that the detection rate of small abnormalities in VE is still below acceptable rates, pointing to the fact that there is still a lot of room for improvement in these procedures. This dissertation proposes alternative techniques for the three phases of creating a VE: image reconstruction, segmentation and animation.

ISBN: 0496567039Subjects--Topical Terms:

626642
Computer Science.

Cone-beam helical CT virtual endoscopy: Reconstruction, segmentation and automatic navigation.
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100 1 $a Carvalho, Bruno Motta de. $3 1932257
245 1 0 $a Cone-beam helical CT virtual endoscopy: Reconstruction, segmentation and automatic navigation.
300 $a 182 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5030.
500 $a Supervisor: Gabor T. Herman.
502 $a Thesis (Ph.D.)--University of Pennsylvania, 2003.
520 $a Virtual Endoscopy (VE) is a technique in which three-dimensional (3D) data, acquired by an imaging technique such as Computerized Tomography (CT) or Magnetic Resonance Imaging (MRI), is segmented and presented in an animation so as to mimic an endoscopic examination, i.e., as if a camera were introduced into an anatomical structure. It has been shown that the detection rate of small abnormalities in VE is still below acceptable rates, pointing to the fact that there is still a lot of room for improvement in these procedures. This dissertation proposes alternative techniques for the three phases of creating a VE: image reconstruction, segmentation and animation.
520 $a We propose the use of Algebraic Reconstruction Techniques (ART), and a block-iterative variation of it (block-ART), for reconstructing 3D images from helical cone-beam CT data. For efficiency and accuracy reasons, we implement ART using modified Kaiser-Bessel window functions (also known as blobs) as basis functions that are placed on the body-centered cubic (bcc) grid, instead of the traditionally used voxels of the simple cubic (sc) grid. The accuracy of the reconstructions produced by these algorithms are compared with the ones produced by a fully-3D filtered backprojection algorithm for several data sets, where is shown that ART produced more accurate reconstructions both in the absence and in the presence of realistic simulated noise.
520 $a For the segmentation step, we propose a general multi-object fuzzy segmentation algorithm that segments a set by producing a map that encodes the grades of membership for all elements of this set for all objects. We report on the accuracy and robustness of our algorithm and present segmentations performed on mathematically-defined images as well as images acquired by various modalities, such as CT and MRI.
520 $a As a result of our segmentation algorithm, strongest "paths" connecting a specific element of the set to any other element of the set are produced. These paths are then smoothed to produce the final navigation paths for the virtual camera of the VE animations.
520 $a In order to show the applicability of our techniques we perform the three phases of generating a VE on a single data set.
590 $a School code: 0175.
650 4 $a Computer Science. $3 626642
650 4 $a Engineering, Biomedical. $3 1017684
650 4 $a Health Sciences, Radiology. $3 1019076
690 $a 0984
690 $a 0541
690 $a 0574
710 2 0 $a University of Pennsylvania. $3 1017401
773 0 $t Dissertation Abstracts International $g 64-10B.
790 1 0 $a Herman, Gabor T., $e advisor
790 $a 0175
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3109160