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

Repeatability characterization and c...

Koozekanani, Dara David.

Linked to FindBook

Google Book

Amazon

博客來

Repeatability characterization and computer vision based analysis of optical coherence tomography.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Repeatability characterization and computer vision based analysis of optical coherence tomography./
Author:	Koozekanani, Dara David.
Description:	230 p.
Notes:	Source: Dissertation Abstracts International, Volume: 62-08, Section: B, page: 3705.
Contained By:	Dissertation Abstracts International62-08B.
Subject:	Engineering, Biomedical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3022516
ISBN:	0493340971

Repeatability characterization and computer vision based analysis of optical coherence tomography.
Koozekanani, Dara David.

Repeatability characterization and computer vision based analysis of optical coherence tomography. - 230 p.

Source: Dissertation Abstracts International, Volume: 62-08, Section: B, page: 3705.

Thesis (Ph.D.)--The Ohio State University, 2001.

Optical coherence tomography is a new imaging technology providing high resolution, cross sectional views of the retina. These images detail microscopic retinal pathology, and are particularly promising for their ability to yield objective, numerical measurements of retinal features in vivo. These measurements may help improve treatment protocols for retinal pathologies involving edema or destruction of tissue layers. However, the measurement repeatability has not been well characterized in the literature. Moreover, there is not a good system available for automatically making thickness measurements from images. Finally, subject motion during scan acquisition causes uncertainty in the precise retinal region imaged. In this dissertation, we address all of these shortcomings, using clinical studies to assess the repeatability and computer vision to present solutions to the other two problems.

ISBN: 0493340971Subjects--Topical Terms:

1017684
Engineering, Biomedical.

Repeatability characterization and computer vision based analysis of optical coherence tomography.
LDR:01866nmm 2200289 4500 001 1837865
005 20050506074605.5
008 130614s2001 eng d
020 $a 0493340971
035 $a (UnM)AAI3022516
035 $a AAI3022516
040 $a UnM $c UnM
100 1 $a Koozekanani, Dara David. $3 1926294
245 1 0 $a Repeatability characterization and computer vision based analysis of optical coherence tomography.
300 $a 230 p.
500 $a Source: Dissertation Abstracts International, Volume: 62-08, Section: B, page: 3705.
500 $a Co-Advisers: Cynthia Roberts; Kim Boyer.
502 $a Thesis (Ph.D.)--The Ohio State University, 2001.
520 $a Optical coherence tomography is a new imaging technology providing high resolution, cross sectional views of the retina. These images detail microscopic retinal pathology, and are particularly promising for their ability to yield objective, numerical measurements of retinal features in vivo. These measurements may help improve treatment protocols for retinal pathologies involving edema or destruction of tissue layers. However, the measurement repeatability has not been well characterized in the literature. Moreover, there is not a good system available for automatically making thickness measurements from images. Finally, subject motion during scan acquisition causes uncertainty in the precise retinal region imaged. In this dissertation, we address all of these shortcomings, using clinical studies to assess the repeatability and computer vision to present solutions to the other two problems.
590 $a School code: 0168.
650 4 $a Engineering, Biomedical. $3 1017684
650 4 $a Health Sciences, Radiology. $3 1019076
690 $a 0541
690 $a 0574
710 2 0 $a The Ohio State University. $3 718944
773 0 $t Dissertation Abstracts International $g 62-08B.
790 1 0 $a Roberts, Cynthia, $e advisor
790 1 0 $a Boyer, Kim, $e advisor
790 $a 0168
791 $a Ph.D.
792 $a 2001
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3022516