本文關(guān)鍵詞： 視網(wǎng)膜血管分割 局部增強(qiáng) 全局增強(qiáng) Zernike矩 多尺度 多模板　出處：《西南交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：人眼視網(wǎng)膜血管形態(tài)結(jié)構(gòu).與多種疾病有著非常密切的聯(lián)系,能夠?yàn)檠劭萍膊∫约叭硇韵到y(tǒng)疾病提供前期診斷和預(yù)防的依據(jù)。傳統(tǒng)的人工篩查,不但工作量大,花費(fèi)大量時(shí)間,而且準(zhǔn)確率較低,并有可能造成誤診。而隨著數(shù)字圖像處理技術(shù)在醫(yī)學(xué)圖像領(lǐng)域的發(fā)展以及計(jì)算機(jī)的廣泛應(yīng)用,視網(wǎng)膜血管結(jié)構(gòu)的自動(dòng)檢測已成為一種趨勢。目前研究者們提出了很多視網(wǎng)膜血管的自動(dòng)分割算法,取得一定成效,但是對血管分割的準(zhǔn)確率及其視網(wǎng)膜自身組織結(jié)構(gòu)的影響有待進(jìn)一步提高。基于此問題,本文提出兩種新的視網(wǎng)膜血管分割算法,并在STARE和DRIVE兩個(gè)圖像庫中進(jìn)行大量實(shí)驗(yàn),最后將實(shí)驗(yàn)結(jié)果和已知的分割算法進(jìn)行比較,論文主要工作如下:1)針對與背景像素對比度較低的細(xì)小血管,其分割準(zhǔn)確率低,造成細(xì)小血管的丟失以及血管斷裂等問題,本文提出了一種基于多尺度的局部與全局增強(qiáng)相結(jié)合的視網(wǎng)膜血管分割算法。首先將多尺度線性檢測器進(jìn)行再劃分,分為小尺度和大尺度兩部分;其次對小尺度下的圖像進(jìn)行局部增強(qiáng)和對大尺度下的圖像進(jìn)行全局增強(qiáng)處理;再次將小尺度下的響應(yīng)函數(shù)以及大尺度下的響應(yīng)函數(shù)與其分別對應(yīng)的增強(qiáng)圖像進(jìn)行線性融合;最終對獲得的融合圖像進(jìn)行后續(xù)處理,去掉非連通區(qū)域和孤立點(diǎn),得到最終的視網(wǎng)膜血管分割圖像。理論分析和實(shí)驗(yàn)結(jié)果表明,本文算法分割出更多的細(xì)小血管,在STARE和DRIVE兩個(gè)圖像庫中的準(zhǔn)確率分別達(dá)到0.9662和0.9645,高于傳統(tǒng)分割算法。2)針對因視盤與視網(wǎng)膜血管結(jié)構(gòu)相似而造成視盤被誤分割為視網(wǎng)膜血管的問題,本文提出了一種基于Zernike矩不同模板系數(shù)的視網(wǎng)膜血管分割算法。首先計(jì)算Zernike矩3×3、5×5、7×7、9×9四個(gè)不同的矩模板系數(shù)M20,并研究不同模板系數(shù)對不同寬度血管的影響;其次對上述四個(gè)模板卷積結(jié)果進(jìn)行多尺度線檢測,得到各模板下的響應(yīng)函數(shù);再次將各自的響應(yīng)函數(shù)與其分別對應(yīng)的矩圖像進(jìn)行線性融合;最后對獲得的融合圖像進(jìn)行后續(xù)處理,去掉非連通區(qū)域和孤立點(diǎn),得到最終的視網(wǎng)膜血管圖像。理論分析和實(shí)驗(yàn)結(jié)果表明,本文算法在STARE和DRIVE兩個(gè)圖像庫中的準(zhǔn)確率分別達(dá)到0.9659和0.9643,且能夠?qū)σ暠P進(jìn)行有效處理。
[Abstract]:The morphological structure of retinal vessels in human eyes is closely related to many diseases and can provide the basis for early diagnosis and prevention of ophthalmic diseases and systemic diseases. Traditional artificial screening. With the development of digital image processing technology in medical image field and the wide application of computer, not only the workload is large, but also the accuracy rate is low, and it may cause misdiagnosis. Automatic detection of retinal vascular structure has become a trend. At present, researchers have proposed a lot of automatic retinal blood vessels segmentation algorithm, and achieved certain results. However, the accuracy of blood vessel segmentation and the influence of retinal tissue structure need to be further improved. Based on this problem, two new retinal vascular segmentation algorithms are proposed in this paper. A large number of experiments are carried out in the STARE and DRIVE image databases. Finally, the experimental results are compared with the known segmentation algorithms. The main work of this paper is as follows: (1) aiming at small blood vessels with low contrast with background pixels, the segmentation accuracy is low, resulting in the loss of small vessels and vascular breakage. In this paper, a multi-scale local and global enhancement based retinal vascular segmentation algorithm is proposed. Firstly, the multi-scale linear detector is subdivided into two parts: small scale and large scale. Secondly, local enhancement of small scale image and global enhancement of large scale image are carried out. Finally, the response function of small scale and the response function of large scale are fused linearly with the corresponding enhancement image. Finally, the fusion image is processed to remove the disconnected region and the isolated point, and the final retinal vascular segmentation image is obtained. The theoretical analysis and experimental results show that. In this paper, more small blood vessels are segmented, and the accuracy in STARE and DRIVE image database is 0.9662 and 0.9645, respectively. Higher than the traditional segmentation algorithm. 2) aiming at the problem that the optic disc is divided into retinal vessels by mistake because of the similarity between the optic disc and the retinal vascular structure. In this paper, a retinal blood vessel segmentation algorithm based on different template coefficients of Zernike moments is proposed. Firstly, the Zernike moment 3 脳 3 脳 5 脳 5 脳 5 脳 7 is calculated. Nine 脳 9 four different moment template coefficients M20, and the effects of different template coefficients on different width of blood vessels were studied. Secondly, the multi-scale line detection is carried out on the convolution results of the above four templates, and the response function under each template is obtained. Thirdly, the corresponding moment images are fused linearly with their respective response functions. Finally, the fusion image is processed to remove the disconnected region and isolated point, and the final retinal vascular image is obtained. The theoretical analysis and experimental results show that. The accuracy of this algorithm in STARE and DRIVE image database is 0.9659 and 0.9643 respectively.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R770.4;TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 朱承璋;鄒北驥;向遙;嚴(yán)權(quán)峰;梁毅雄;崔錦愷;劉晴;;彩色眼底圖像視網(wǎng)膜血管分割方法研究進(jìn)展[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2015年11期

2 單玲玉;閔鋒;李延達(dá);;全局閾值與局部閾值相結(jié)合的視網(wǎng)膜血管分割方法[J];武漢工程大學(xué)學(xué)報(bào);2015年03期

3 唐堅(jiān)剛;林新;任琳;李春;;一種改進(jìn)的亞像素邊緣檢測方法[J];信息技術(shù);2014年03期

4 高向軍;;基于多尺度線性檢測的視網(wǎng)膜血管分割[J];科學(xué)技術(shù)與工程;2013年23期

5 武阿明;張奇志;周亞麗;;基于小波和Zernike邊緣提取[J];北京信息科技大學(xué)學(xué)報(bào)(自然科學(xué)版);2013年04期

6 王俊平;李錦;;圖像對比度增強(qiáng)研究的進(jìn)展[J];電子科技;2013年05期

7 高瑋瑋;沈建新;王玉亮;;基于數(shù)學(xué)形態(tài)學(xué)的快速糖尿病視網(wǎng)膜病變自動(dòng)檢測方法[J];光譜學(xué)與光譜分析;2012年03期

8 高福友;;生物特征識別技術(shù)及其在監(jiān)獄安全防范領(lǐng)域的應(yīng)用[J];安防科技;2011年02期

9 馬新;陳松燦;;彩色視網(wǎng)膜圖像中基于主血管網(wǎng)的視盤定位[J];江南大學(xué)學(xué)報(bào)(自然科學(xué)版);2010年01期

10 王芳;;基于生物特征的身份認(rèn)證技術(shù)研究與發(fā)展[J];科技信息;2009年28期

，

本文編號：1472754