Automatic Detection of Abnormal Lymph Nodes and Glands in Neck CT Images

碩士 === 國立交通大學 === 電控工程研究所 === 100 === In the medical images, computerized tomography (CT) technology is used in radiological examinations, and neck CT scanning inspection is often applied in research of neck tumors or masses as well as in searching for the cervical lymph node to be tumescent; h...

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Bibliographic Details
Main Author: 陳俊良
Other Authors: 林昇甫
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/96819326209042070020
Description
Summary:碩士 === 國立交通大學 === 電控工程研究所 === 100 === In the medical images, computerized tomography (CT) technology is used in radiological examinations, and neck CT scanning inspection is often applied in research of neck tumors or masses as well as in searching for the cervical lymph node to be tumescent; however, due to the fact that tissue of neck CT is complex, doctors are often confused about the correct location and size of the lesion when they are diagnosing, and then trapped into a stalemated situation. The purpose of this study is the use of image processing and information technology for automatically computer-aided medical analysis on neck CT images, and displays the results on a computer screen or medical instruments. By this way, doctors are allowed to understand the patient's situation more quickly. Moreover, this technology not only alleviates the burden on doctors, but also promotes the efficiency. The main contribution of this paper is as follows: First, this paper uses a suitable analysis method on soft tissues of the neck CT image to improve the shortcoming when partitioning them, and effectively distinguish the abnormal lymph nodes and soft tissue. Second, this paper proposes a prototype and methods to assist the process of lesion detection. In this thesis, the final experimental results show that the computer-aided diagnosis system in the neck CT imaging can effectively identify the suspicious block of suspected lesions and provide doctors with simpler and effective assistant diagnostic information.