植基於改良Level Set演算法之CT影像的肝臟自動切割

Automatic segmentation of the liver based on improved Level set method in CT images

詹益典(Yi-Tien Zhan)

指導教授 ： 林春宏

共同指導教授 ： 黃馨逸(Hsin-I Huang)

國立臺中科技大學/資訊與流通學院/資訊管理系碩士班/碩士(2014年)

https://doi.org/10.6826/NUTC.2014.00083

摘要

本研究提出一個新的醫學影像切割方法，改良了Level set切割法，將肝臟從電腦斷層(CT)影像中快速且正確切割出來。本研究之切割法分為肝臟初步輪廓偵測以及肝臟Level set切割。肝臟初步輪廓偵測係採用醫療影像專用DICOM格式中的Hounsfield Unit（HU），提取肝臟的窗寬與窗高來設定閥值，然後進行二值化，再進行形態學技術完成肝臟初步輪廓的切割。肝臟Level set切割方法係利用肝臟初步輪廓進行Level set的處理，以取得較精確的肝臟輪廓。實驗證明本文方法的肝臟偵測的準確率相當高，而且肝臟的切割準確率也高達95.23%。本文方法能提升肝臟切割的準確度並且減少處理的時間，全程使用DICOM格式影像來進行切割，也方便應用在醫院內的PACS系統之中，期望能實際應用在臨床醫師輔助判讀之用。

關鍵字

Level set ； 肝臟 ； DICOM ； 影像切割 ； 電腦斷層影像

並列摘要

This study proposes a new method for medical image segmentation, automatic Level set cutting method, the liver from computed tomography (CT) images quickly and accurately cut out. Automatic liver cut method of this study will be divided into a preliminary outline of the liver and liver Level set to detect cut. Liver preliminary outline detection system using a dedicated medical images in DICOM format Hounsfield Unit (HU), extracting the liver window width and window level to set the threshold, and morphological techniques to complete the initial liver contour cutting. Cut liver Level set method takes advantage liver contour Level set of initial treatment to obtain more precise liver profile. Experiments show that the proposed method to detect liver accuracy rate is very high, and cutting accuracy rate as high as 95.23% of the liver. This method can improve the accuracy and reduce the liver cut processing time, full use of DICOM format images to be cut into convenient in-hospital PACS system, hoping to assist interpretation of the practical applications for use in clinical physician.

並列關鍵字

Level set ； liver ； DICOM ； Image segmentation ； CT

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