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Three-dimensional bone geometry reco...

Gunay, Murat.

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Three-dimensional bone geometry reconstruction from x-ray images using hierarchical free-form deformation and non-linear optimization.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Three-dimensional bone geometry reconstruction from x-ray images using hierarchical free-form deformation and non-linear optimization./
Author:	Gunay, Murat.
Description:	141 p.
Notes:	Adviser: Kenji Shimada.
Contained By:	Dissertation Abstracts International63-12B.
Subject:	Engineering, Industrial. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3074893
ISBN:	0493950737

Three-dimensional bone geometry reconstruction from x-ray images using hierarchical free-form deformation and non-linear optimization.
Gunay, Murat.

Three-dimensional bone geometry reconstruction from x-ray images using hierarchical free-form deformation and non-linear optimization. - 141 p.

Adviser: Kenji Shimada.

Thesis (Ph.D.)--Carnegie Mellon University, 2003.

This thesis presents a cost and time effective computational method for generating a three-dimensional bone shape from multiple x-ray images. Starting with a predefined three-dimensional template bone shape, whose shape is clinically normal and scaled to an average size, our method scales, and deforms the template shape until the deformed shape gives an image similar to an input x-ray image when projected onto a two-dimensional plane. We use hierarchical free form deformation to scale and deform the template bone, and a deformation in each deformation layer is controlled by eight variables. The problem of finding the three-dimensional shape of the bone is thus reduced to a sequence of optimization problems with eight design variables; our objective is to minimize the error, or the difference between the input x-ray image and the projected image of the deformed template shape. We use sequential quadratic programming (SQP) to solve this multidimensional optimization problem. The proposed x-ray image based shape reconstruction is more computationally efficient, cost effective, and portable compared to standard three-dimensional sensor based methods, such as computerized tomography (CT) and magnetic resonance imaging (MRI). Although the final three-dimensional shape of our method can be less accurate than using CT and MRI, because of our minimum input of x-ray images, our method creates a three-dimensional shape accurate enough for many applications such as: (1) making a three-dimensional physical mockup for training, and (2) importing into and using in a computer aided planning system for orthopedic surgery, including bone distraction and open/closed wedge osteotomy.

ISBN: 0493950737Subjects--Topical Terms:

626639
Engineering, Industrial.

Three-dimensional bone geometry reconstruction from x-ray images using hierarchical free-form deformation and non-linear optimization.
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100 1 $a Gunay, Murat. $3 1250956
245 1 0 $a Three-dimensional bone geometry reconstruction from x-ray images using hierarchical free-form deformation and non-linear optimization.
300 $a 141 p.
500 $a Adviser: Kenji Shimada.
500 $a Source: Dissertation Abstracts International, Volume: 63-12, Section: B, page: 6054.
502 $a Thesis (Ph.D.)--Carnegie Mellon University, 2003.
520 $a This thesis presents a cost and time effective computational method for generating a three-dimensional bone shape from multiple x-ray images. Starting with a predefined three-dimensional template bone shape, whose shape is clinically normal and scaled to an average size, our method scales, and deforms the template shape until the deformed shape gives an image similar to an input x-ray image when projected onto a two-dimensional plane. We use hierarchical free form deformation to scale and deform the template bone, and a deformation in each deformation layer is controlled by eight variables. The problem of finding the three-dimensional shape of the bone is thus reduced to a sequence of optimization problems with eight design variables; our objective is to minimize the error, or the difference between the input x-ray image and the projected image of the deformed template shape. We use sequential quadratic programming (SQP) to solve this multidimensional optimization problem. The proposed x-ray image based shape reconstruction is more computationally efficient, cost effective, and portable compared to standard three-dimensional sensor based methods, such as computerized tomography (CT) and magnetic resonance imaging (MRI). Although the final three-dimensional shape of our method can be less accurate than using CT and MRI, because of our minimum input of x-ray images, our method creates a three-dimensional shape accurate enough for many applications such as: (1) making a three-dimensional physical mockup for training, and (2) importing into and using in a computer aided planning system for orthopedic surgery, including bone distraction and open/closed wedge osteotomy.
590 $a School code: 0041.
650 4 $a Engineering, Industrial. $3 626639
650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Health Sciences, Medicine and Surgery. $3 1017756
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710 2 0 $a Carnegie Mellon University. $3 1018096
773 0 $t Dissertation Abstracts International $g 63-12B.
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790 1 0 $a Shimada, Kenji, $e advisor
791 $a Ph.D.
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