自動化胸部X光影像肺結節偵測之研究

Automated Detection of Lung Nodules in Chest X-ray Images

王譽潔(Yu-Jie Wang)

指導教授 ： 郭文嘉

元智大學/資訊學院/資訊管理學系/碩士(2011年)

摘要

惡性腫瘤為近年來國人十大死因之首，其中肺癌位居首位，若能在初期發現、及早治療，將具有較佳的治癒效果。本論文主要目的在利用胸部X光影像中建立一套電腦輔助偵測系統，主要應用影像處理的技術在X光影像上，用以輔助醫師診斷肺結節之位置。本研究中主要分為三個部份，第一部分利用直方圖(Histogram)方法找出其肺部區域，第二部份則為區域成長(Region Growing)找出肺部輪廓位置，最後利用圓形偵測方式找出結節位置。從實驗結果顯示，本論文提出之電腦輔助偵測系統對於偵測肺部結節位置的在平均候選個數為47.7時準確率(Accuracy)可達82.47%，而在各級微妙度上，可行類(Practicable)包含明顯、較為明顯以及微妙此三級微妙度之準確度為86%，困難處理(Hard)包含非常微妙以及極微妙此兩級之準確度為76%，證實本論文所提出的電腦診斷輔助系統對於醫師在偵測較不易觀察之肺部結節位置上可提供有效之協助。

關鍵字

肺癌 ； 肺結節 ； 胸部X光影像 ； 圓形偵測 ； Hough轉換

並列摘要

In the past few years, malignant tumor has been a primary factory that which causes death. According to the statistics, lung cancer is the most frequently suffered disease among different cancers. In this paper, we develop a computer-aided detection (CAD) system for the detection of lung nodules in chest X-ray images. There are three main steps in this study. First, the lung areas are marked based on the histogram information. Second, we use the region growing method to find the contour of lung area. Finally, locations of nodule candidates are marked with circle detection method. Moreover, improper candidates are removed by the elimination criteria. Experimental results show that the average candidates are 47.7 per image with the accuracy of 82.47% to find lung nodules. In every subtle degree, the accuracy of the practicable degree and the hard degree were 86% and 76%, respectively. The proposed method showed the capability of enhancing the accuracy for the detection of subtle nodules.

並列關鍵字

Hough Transform ； Lung Cancer ； Lung Nodule ； Chest X-ray Image ； Circular Detection

參考文獻

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