Implementation of Lung Extraction Based on the Structure of Lung Nodule Computer Aided Diagnosis System
碩士 === 元智大學 === 資訊管理學系 === 99 === The primary function of the CAD system is to help doctors identify those images with suspicious pathological lung regions, make precise diagnoses, and successfully cure lung cancer patients. Therefore, this thesis has collected a great number of correlated theories...
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ndltd-TW-099YZU053960342016-04-13T04:17:15Z http://ndltd.ncl.edu.tw/handle/92812430324866834344 Implementation of Lung Extraction Based on the Structure of Lung Nodule Computer Aided Diagnosis System 基於肺腫瘤電腦輔助系統診斷架構下之肺區擷取實作 Yu-Shen Tsai 蔡祐慎 碩士 元智大學 資訊管理學系 99 The primary function of the CAD system is to help doctors identify those images with suspicious pathological lung regions, make precise diagnoses, and successfully cure lung cancer patients. Therefore, this thesis has collected a great number of correlated theories and research papers, aims to construct a complete structure of the CAD system, which is usually supported by a Rule-based system or Neural Network architectures, for doctors and radiologists to make effective diagnoses of lung cancer patients. However, limited by time and money, this thesis only operates the first step of the CAD system, which is the lung region extraction. Although this thesis only focuses on the lung region extraction, and thus cannot execute every step of the CAD system, it can still serve as a useful and valuable example for those who are interested in the implementation of the following steps of the CAD system. In fact, the results of lung region extraction can deeply influence later diagnoses and evaluations. Consequently, if lung region extraction can be successfully accomplished, it will definitely help the following steps of the CAD system implementation work more functionally. 盧以詮 2011 學位論文 ; thesis 65 en_US |
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碩士 === 元智大學 === 資訊管理學系 === 99 === The primary function of the CAD system is to help doctors identify those images with suspicious pathological lung regions, make precise diagnoses, and successfully cure lung cancer patients. Therefore, this thesis has collected a great number of correlated theories and research papers, aims to construct a complete structure of the CAD system, which is usually supported by a Rule-based system or Neural Network architectures, for doctors and radiologists to make effective diagnoses of lung cancer patients. However, limited by time and money, this thesis only operates the first step of the CAD system, which is the lung region extraction. Although this thesis only focuses on the lung region extraction, and thus cannot execute every step of the CAD system, it can still serve as a useful and valuable example for those who are interested in the implementation of the following steps of the CAD system. In fact, the results of lung region extraction can deeply influence later diagnoses and evaluations. Consequently, if lung region extraction can be successfully accomplished, it will definitely help the following steps of the CAD system implementation work more functionally.
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author2 |
盧以詮 |
author_facet |
盧以詮 Yu-Shen Tsai 蔡祐慎 |
author |
Yu-Shen Tsai 蔡祐慎 |
spellingShingle |
Yu-Shen Tsai 蔡祐慎 Implementation of Lung Extraction Based on the Structure of Lung Nodule Computer Aided Diagnosis System |
author_sort |
Yu-Shen Tsai |
title |
Implementation of Lung Extraction Based on the Structure of Lung Nodule Computer Aided Diagnosis System |
title_short |
Implementation of Lung Extraction Based on the Structure of Lung Nodule Computer Aided Diagnosis System |
title_full |
Implementation of Lung Extraction Based on the Structure of Lung Nodule Computer Aided Diagnosis System |
title_fullStr |
Implementation of Lung Extraction Based on the Structure of Lung Nodule Computer Aided Diagnosis System |
title_full_unstemmed |
Implementation of Lung Extraction Based on the Structure of Lung Nodule Computer Aided Diagnosis System |
title_sort |
implementation of lung extraction based on the structure of lung nodule computer aided diagnosis system |
publishDate |
2011 |
url |
http://ndltd.ncl.edu.tw/handle/92812430324866834344 |
work_keys_str_mv |
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