北京生物醫(yī)學工程

基于CT三維圖像的肺結(jié)節(jié)良惡性鑒別研究

Identification of benign and malignant pulmonary nodule based on 3D CT image

作者：常莎王瑞平

單位：                      北京交通大學計算機與信息技術(shù)學院 (北京100044)        

關(guān)鍵詞：肺部；CT圖像；三維重建；良惡性結(jié)節(jié)；支持向量機

分類號：

出版年·卷·期（頁碼）：2013·32·1（12-16）

摘要：

目的運用計算機方法處理肺部CT圖像以識別肺結(jié)節(jié)良惡性并輔助肺癌診斷，現(xiàn)已成為國內(nèi)外研究的熱點。方法提出一種基于肺部CT圖像三維肺結(jié)節(jié)信息的肺結(jié)節(jié)良惡性鑒別方法。首先結(jié)合閾值分割、區(qū)域生長、形態(tài)學運算等在CT圖像上分割出肺結(jié)節(jié)，進而提取每個肺結(jié)節(jié)的三維特征并優(yōu)化，選擇有效特征。然后，基于有效特征采用支持向量機(support vector machine, SVM)的分類算法對多維向量所描述的肺結(jié)節(jié)進行良惡性的二分類。最后從敏感性、特異性、準確率以及似然比等方面全面評估分類結(jié)果。結(jié)果實驗獲得敏感性為0.7776，準確性為0.7378，陽性似然比2.2410，陰性似然比0.3682，顯示基于CT三維肺結(jié)節(jié)圖像可以達到令人滿意的肺部腫瘤良、惡性鑒別效果。結(jié)論上述結(jié)果證明了基于CT三維圖像的肺結(jié)節(jié)良惡性鑒別方法的可行性。本研究對計算機輔助肺癌的診斷具有重要意義。

Objective Identification of benign and malignant pulmonary nodules by using the computer-aided detection and diagnosis system is one hot spot. Methods An identification method for benign and malignant pulmonary nodule based on the 3D information of lung CT image was proposed. First we segmented the pulmonary nodules from CT images with the methods of segmentation, regional growth, morphology, then extracted and optimized the 3D information of each pulmonary nodule. Finally we utilized the SVM classification algorithm to divide those pulmonary nodules into two categories based on the effective features. Results The classification results were assessed by sensitivity, specificity, accuracy, and likelihood ratio. From the experiment we got the results as follows, the sensitivity was 0.7776, the accuracy was 0.7378, the positive likelihood ratio was 2.2410 and the negative likelihood ratio was 0.3682. Conclusions All the results showed that the new method achieved satisfactory identification effect and was significant for the computer-aided diagnosis of lung cancer.

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