東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Computerized segmentation and measur...

Sensakovic, William F.

FindBook

Google Book

Amazon

博客來

Computerized segmentation and measurement of pleural disease.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Computerized segmentation and measurement of pleural disease./
作者:	Sensakovic, William F.
面頁冊數:	253 p.
附註:	Source: Dissertation Abstracts International, Volume: 71-07, Section: B, page: 4120.
Contained By:	Dissertation Abstracts International71-07B.
標題:	Biophysics, Medical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3408665
ISBN:	9781124050959

Computerized segmentation and measurement of pleural disease.
Sensakovic, William F.

Computerized segmentation and measurement of pleural disease. - 253 p.

Source: Dissertation Abstracts International, Volume: 71-07, Section: B, page: 4120.

Thesis (Ph.D.)--The University of Chicago, 2010.

The measurement of disease extent is vital for tracking disease progression and determining treatment efficacy. Current methods for measuring pleural disease extent do not take advantage of the volumetric measurements possible on modern computed tomography (CT) scans because of the time necessary for manual disease delineation. This dissertation describes computerized methods to three-dimensionally (3D) segment and volumetrically measure pleural disease. Novel and robust automated methods to segment the thoracic skin boundary, airway, and lung parenchyma were developed and specific techniques created for these the segmentation methods may find application in other computerized systems and imaging modalities. The lung parenchyma segmentation method was implemented to confirm the ability of surgical intervention to free lung that is restricted by pleural disease. A novel hemithoracic cavity segmentation method was developed which requires minimal user initialization and delineates the cavities in 3D from automatically identified boundary structures. Finally, a pleural disease segmentation method was developed which delineates pleural disease in 3D and calculates disease volume. The computer-derived segmentations and volume estimates demonstrated good agreement with observer-defined disease delineations. In addition to the development and application of the computerized methods, several studies related to the underlying theory of computerized segmentation and disease measurement were conducted. The selection of corresponding sections on serial CT scans was identified as a source of variability when the current standard (linear measurement) is used to measure disease extent. This variability was quantified and an automated registration method is implemented as a potential solution. The mathematical definitions of boundary and area were investigated as a source of measurement bias and variability. Finally, the influence that an initial segmentation has on observer-defined segmentations was quantified and the strong influence raises several questions related to the ability of observers to correct computer-generated outlines used both for determining disease extent and delineating treatment volumes for radiation therapy. This dissertation developed and investigated a novel method for the computerized segmentation of pleural disease. These methods will form the basis of a system that we hope will allow researchers and clinicians to efficiently segment and measure pleural disease to monitor disease progression and evaluate treatment efficacy.

ISBN: 9781124050959Subjects--Topical Terms:

1017681
Biophysics, Medical.

Computerized segmentation and measurement of pleural disease.
LDR:03633nam 2200325 4500 001 1399856
005 20110930095850.5
008 130515s2010 ||||||||||||||||| ||eng d
020 $a 9781124050959
035 $a (UMI)AAI3408665
035 $a AAI3408665
040 $a UMI $c UMI
100 1 $a Sensakovic, William F. $3 1678869
245 1 0 $a Computerized segmentation and measurement of pleural disease.
300 $a 253 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-07, Section: B, page: 4120.
500 $a Adviser: Samuel G. Armato.
502 $a Thesis (Ph.D.)--The University of Chicago, 2010.
520 $a The measurement of disease extent is vital for tracking disease progression and determining treatment efficacy. Current methods for measuring pleural disease extent do not take advantage of the volumetric measurements possible on modern computed tomography (CT) scans because of the time necessary for manual disease delineation. This dissertation describes computerized methods to three-dimensionally (3D) segment and volumetrically measure pleural disease. Novel and robust automated methods to segment the thoracic skin boundary, airway, and lung parenchyma were developed and specific techniques created for these the segmentation methods may find application in other computerized systems and imaging modalities. The lung parenchyma segmentation method was implemented to confirm the ability of surgical intervention to free lung that is restricted by pleural disease. A novel hemithoracic cavity segmentation method was developed which requires minimal user initialization and delineates the cavities in 3D from automatically identified boundary structures. Finally, a pleural disease segmentation method was developed which delineates pleural disease in 3D and calculates disease volume. The computer-derived segmentations and volume estimates demonstrated good agreement with observer-defined disease delineations. In addition to the development and application of the computerized methods, several studies related to the underlying theory of computerized segmentation and disease measurement were conducted. The selection of corresponding sections on serial CT scans was identified as a source of variability when the current standard (linear measurement) is used to measure disease extent. This variability was quantified and an automated registration method is implemented as a potential solution. The mathematical definitions of boundary and area were investigated as a source of measurement bias and variability. Finally, the influence that an initial segmentation has on observer-defined segmentations was quantified and the strong influence raises several questions related to the ability of observers to correct computer-generated outlines used both for determining disease extent and delineating treatment volumes for radiation therapy. This dissertation developed and investigated a novel method for the computerized segmentation of pleural disease. These methods will form the basis of a system that we hope will allow researchers and clinicians to efficiently segment and measure pleural disease to monitor disease progression and evaluate treatment efficacy.
590 $a School code: 0330.
650 4 $a Biophysics, Medical. $3 1017681
650 4 $a Computer Science. $3 626642
650 4 $a Health Sciences, Oncology. $3 1018566
690 $a 0760
690 $a 0984
690 $a 0992
710 2 $a The University of Chicago. $b Medical Physics. $3 1671030
773 0 $t Dissertation Abstracts International $g 71-07B.
790 1 0 $a Armato, Samuel G., $e advisor
790 1 0 $a Giger, Maryellen L. $e committee member
790 1 0 $a MacMahon, Heber $e committee member
790 1 0 $a Kindler, Hedy L. $e committee member
790 $a 0330
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3408665