發(fā)布時間：2019-05-30 06:57

【摘要】：乳腺X線圖像腫塊的良惡性分類是計算機輔助診斷的研究內(nèi)容之一,本文對乳腺X線圖像腫塊邊緣分割及不同特征的腫塊良惡性分類進行研究.基于最大化分割后圖像類間方差的思想,提出了一種改進控制標記分水嶺方法完成粗分割,然后采用無邊緣活動輪廓(CV)模型對粗分割結(jié)果進行修正.為了驗證不同特征在腫塊良惡性分類中的性能,對現(xiàn)有形狀特征、紋理特征在不同分類器下的分類性能進行測試.實驗在開源數(shù)據(jù)庫DDSM上驗證,結(jié)果表明,在通過自動分割方法得到腫塊邊緣的情況下,紋理特征的分類性能更好.
[Abstract]:The classification of benign and malignant breast X-ray masses is one of the research contents of computer aided diagnosis. In this paper, the edge segmentation of breast X-ray masses and the classification of benign and malignant masses with different characteristics were studied. Based on the idea of maximizing the inter-class variance of images after segmentation, an improved control mark watershed method is proposed to complete rough segmentation, and then the rough segmentation results are modified by (CV) model without edge active contours. In order to verify the performance of different features in the classification of benign and malignant masses, the classification performance of existing shape features and texture features under different classifiers was tested. The experiment is verified on the open source database DDSM. The results show that the classification performance of texture features is better when the edge of the mass is obtained by automatic segmentation.
【作者單位】： 北京交通大學電子信息工程學院;
【基金】：國家自然科學基金項目(61502025,61571036) 中國博士后科學基金項目(2015M570029) 北京交通大學人才基金(2015RC024) 中央高校基本科研業(yè)務(wù)費專項資金(2016JBM010)~~
【分類號】：R730.44;R737.9;TP391.41

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相關(guān)碩士學位論文 前2條

1 顧曉雯;單、雙指數(shù)擴散加權(quán)成像在肺結(jié)節(jié)/腫塊良惡性鑒別中的初步探討[D];南通大學;2016年

2 侯慧;基于分水嶺算法的白細胞分割研究[D];湘潭大學;2016年

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本文編號：2488621