東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

On constrained contour energy minimi...

Wang, Xun.

Linked to FindBook

Google Book

Amazon

博客來

On constrained contour energy minimization: A new approach to deformable contour methods.

Record Type:	Electronic resources : Monograph/item
Title/Author:	On constrained contour energy minimization: A new approach to deformable contour methods./
Author:	Wang, Xun.
Description:	118 p.
Notes:	Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1642.
Contained By:	Dissertation Abstracts International66-03B.
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3168753
ISBN:	9780542053214

On constrained contour energy minimization: A new approach to deformable contour methods.
Wang, Xun.

On constrained contour energy minimization: A new approach to deformable contour methods. - 118 p.

Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1642.

Thesis (Ph.D.)--University of Cincinnati, 2005.

The dissertation presents a constrained optimization approach to contour energy minimization problems for deformable contour methods. The approach introduces a constraint of region features into the boundary based contour energy minimization framework. In this approach, the contour energy to be minimized can be arbitrary function characterizing target boundary and the constraint can be functions of any region features characterizing the contour interiors. Three deformable contour methods, respectively derived from evolution strategy, variational method, and divide and conquer approaches are proposed to solve the constrained contour energy minimization problem. Among the three deformable contour methods, evolution strategy iteratively generates a population of contour individuals by adding stochastic perturbations to contour evolutions and selects the optimal solutions; Variational method takes a Lagrange approach and minimizes the Lagrange function by a derivative based approach; Divide and conquer approach divides the contour into segments, and then iteratively deforms each contour segment under the region constraint and select the contour with minimum contour energy. The methods are successfully applied to MRI brain, ultrasound pig heart, CT abdominal, and microscopic blood cell images with contours having gaps, blur segments, complex shape, and inhomogeneous interiors. More favorable results comparing to other conventional deformable contour methods are also demonstrated.

ISBN: 9780542053214Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

On constrained contour energy minimization: A new approach to deformable contour methods.
LDR:02379nmm 2200265 4500 001 1824190
005 20061128083228.5
008 130610s2005 eng d
020 $a 9780542053214
035 $a (UnM)AAI3168753
035 $a AAI3168753
040 $a UnM $c UnM
100 1 $a Wang, Xun. $3 1681881
245 1 0 $a On constrained contour energy minimization: A new approach to deformable contour methods.
300 $a 118 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1642.
500 $a Chair: William G. Wee.
502 $a Thesis (Ph.D.)--University of Cincinnati, 2005.
520 $a The dissertation presents a constrained optimization approach to contour energy minimization problems for deformable contour methods. The approach introduces a constraint of region features into the boundary based contour energy minimization framework. In this approach, the contour energy to be minimized can be arbitrary function characterizing target boundary and the constraint can be functions of any region features characterizing the contour interiors. Three deformable contour methods, respectively derived from evolution strategy, variational method, and divide and conquer approaches are proposed to solve the constrained contour energy minimization problem. Among the three deformable contour methods, evolution strategy iteratively generates a population of contour individuals by adding stochastic perturbations to contour evolutions and selects the optimal solutions; Variational method takes a Lagrange approach and minimizes the Lagrange function by a derivative based approach; Divide and conquer approach divides the contour into segments, and then iteratively deforms each contour segment under the region constraint and select the contour with minimum contour energy. The methods are successfully applied to MRI brain, ultrasound pig heart, CT abdominal, and microscopic blood cell images with contours having gaps, blur segments, complex shape, and inhomogeneous interiors. More favorable results comparing to other conventional deformable contour methods are also demonstrated.
590 $a School code: 0045.
650 4 $a Engineering, Electronics and Electrical. $3 626636
690 $a 0544
710 2 0 $a University of Cincinnati. $3 960309
773 0 $t Dissertation Abstracts International $g 66-03B.
790 1 0 $a Wee, William G., $e advisor
790 $a 0045
791 $a Ph.D.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3168753