眼底圖像中視盤的定位與分割方法研究
發(fā)布時間：2018-07-25 07:51
【摘要】：眼底是觀察全身疾病的“窗口”,高血壓、高血脂、腎炎、糖尿病、中樞神經(jīng)系統(tǒng)等許多疾病均會引發(fā)眼底病變,因此基于眼底圖像的疾病早期篩查和檢測越來越受到重視。視盤是眼底圖像的一個重要特征,對其進(jìn)行準(zhǔn)確、快速地定位與分割對利用眼底圖像進(jìn)行疾病輔助診斷具有重要意義。在兼顧定位與分割準(zhǔn)確性的同時,本文所研究的算法著重關(guān)注計(jì)算速度以滿足實(shí)際系統(tǒng)對實(shí)時性的要求,為此主要從感興趣區(qū)域確定、視盤候選區(qū)選取和血管擦除三方面進(jìn)行了算法改進(jìn)。具體研究內(nèi)容如下:(1)預(yù)處理方面,在眼底圖像的紅色分量中使用大津閾值分割法生成感興趣區(qū)域掩膜圖像,使用雙線性插值法將感興趣區(qū)域的邊長縮放至540個像素;(2)血管分割方面,在眼底圖像的綠色分量上對比四種對比度增強(qiáng)算法,選取了速度快且效果優(yōu)秀的CLAHE(Contrast Limited Adaptive Histogram Equalization)方法。對比了基于自適應(yīng)直方圖均衡及形態(tài)學(xué)底帽變換的兩種血管增強(qiáng)算法,選擇了耗時較短的后者。在增強(qiáng)結(jié)果上使用大津閾值分割得到血管圖像;(3)視盤定位方面,基于血管分割結(jié)果對感興趣區(qū)域進(jìn)行取半操作以減少后續(xù)計(jì)算量。依據(jù)視盤的亮度特性,使用DLC(Directional Local Contrast)算法獲取眼底圖像中的亮斑區(qū)域作為視盤候選區(qū),隨后依據(jù)視盤的血管特性選取出血管分支數(shù)最多的候選區(qū)為視盤區(qū)域,取該區(qū)域重心坐標(biāo)為視盤中心定位結(jié)果;(4)視盤分割方面,結(jié)合形態(tài)學(xué)方法與插值方法得到了快速有效的血管擦除方法,在血管擦除結(jié)果上使用Canny算子進(jìn)行邊緣檢測,使用Hough變換得到視盤分割結(jié)果。最后完成了對包含不同眼底病變的MESSIDOR眼底圖像庫(1200張眼底圖像)的測試。結(jié)果表明,本文研究的算法具有較好的視盤定位效果,得到了99%的準(zhǔn)確率,平均用時0.777s。在定位正確的結(jié)果上進(jìn)一步得到了較好的分割效果,平均耗時0.295s。因此,可以說本文研究的視盤定位與分割算法具有復(fù)雜度低、速度快,準(zhǔn)確率高等優(yōu)點(diǎn),相對其它方法更符合實(shí)際系統(tǒng)實(shí)時處理要求。
[Abstract]:Fundus is the "window" to observe systemic diseases. Many diseases such as hypertension, hyperlipidemia, nephritis, diabetes, central nervous system and so on can cause fundus diseases. Therefore, the early screening and detection of diseases based on fundus image are paid more and more attention. Optical disc is an important feature of fundus image. It is very important to locate and segment the image accurately and quickly for the diagnosis of disease using fundus image. While taking into account the accuracy of location and segmentation, the algorithm studied in this paper focuses on the calculation speed to meet the real-time requirements of the actual system, so it is mainly determined from the region of interest. The algorithm is improved in three aspects: the selection of disc candidate area and vascular erasure. The specific research contents are as follows: (1) in the aspect of preprocessing, the region of interest mask image is generated by using Otsu threshold segmentation method in the red component of the fundus image. Bilinear interpolation is used to scale the edge length of the region of interest to 540 pixels. (2) in the aspect of blood vessel segmentation, four contrast enhancement algorithms are compared in the green component of the fundus image, and the fast and excellent CLAHE (Contrast Limited Adaptive Histogram Equalization) method is selected. Two kinds of vascular enhancement algorithms based on adaptive histogram equalization and morphological bottom hat transform are compared. In contrast to the enhancement results, we use the Otsu threshold to segment the vascular images. (3) in the aspect of visual disk location, the region of interest is half-operated based on the segmentation results to reduce the amount of subsequent computation. According to the luminance characteristics of the disc, the bright spot area in the fundus image is obtained by DLC (Directional Local Contrast) algorithm as the candidate area of the disc, and then the candidate region with the largest number of vascular branches is selected as the visual disk area according to the vascular characteristics of the disc. The center of gravity of the region is taken as the center of the visual disk. (4) in the field of disk segmentation, a fast and effective vascular erasure method is obtained by combining morphological method with interpolation method, and the edge detection is performed by using Canny operator on the result of vascular erasure. The Hough transform is used to get the result of the disk segmentation. Finally, the MESSIDOR fundus image library (1200 fundus images) with different fundus lesions was tested. The results show that the algorithm presented in this paper has a good location effect, and the accuracy is 99%. The average time used is 0.777s. A better segmentation effect was obtained on the basis of correct localization results, with an average time of 0.295 s. Therefore, it can be said that the video disk localization and segmentation algorithm studied in this paper has the advantages of low complexity, high speed, high accuracy and so on. Compared with other methods, it is more suitable for real time processing of real time system.
【學(xué)位授予單位】：沈陽工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41
本文編號：2143137
[Abstract]:Fundus is the "window" to observe systemic diseases. Many diseases such as hypertension, hyperlipidemia, nephritis, diabetes, central nervous system and so on can cause fundus diseases. Therefore, the early screening and detection of diseases based on fundus image are paid more and more attention. Optical disc is an important feature of fundus image. It is very important to locate and segment the image accurately and quickly for the diagnosis of disease using fundus image. While taking into account the accuracy of location and segmentation, the algorithm studied in this paper focuses on the calculation speed to meet the real-time requirements of the actual system, so it is mainly determined from the region of interest. The algorithm is improved in three aspects: the selection of disc candidate area and vascular erasure. The specific research contents are as follows: (1) in the aspect of preprocessing, the region of interest mask image is generated by using Otsu threshold segmentation method in the red component of the fundus image. Bilinear interpolation is used to scale the edge length of the region of interest to 540 pixels. (2) in the aspect of blood vessel segmentation, four contrast enhancement algorithms are compared in the green component of the fundus image, and the fast and excellent CLAHE (Contrast Limited Adaptive Histogram Equalization) method is selected. Two kinds of vascular enhancement algorithms based on adaptive histogram equalization and morphological bottom hat transform are compared. In contrast to the enhancement results, we use the Otsu threshold to segment the vascular images. (3) in the aspect of visual disk location, the region of interest is half-operated based on the segmentation results to reduce the amount of subsequent computation. According to the luminance characteristics of the disc, the bright spot area in the fundus image is obtained by DLC (Directional Local Contrast) algorithm as the candidate area of the disc, and then the candidate region with the largest number of vascular branches is selected as the visual disk area according to the vascular characteristics of the disc. The center of gravity of the region is taken as the center of the visual disk. (4) in the field of disk segmentation, a fast and effective vascular erasure method is obtained by combining morphological method with interpolation method, and the edge detection is performed by using Canny operator on the result of vascular erasure. The Hough transform is used to get the result of the disk segmentation. Finally, the MESSIDOR fundus image library (1200 fundus images) with different fundus lesions was tested. The results show that the algorithm presented in this paper has a good location effect, and the accuracy is 99%. The average time used is 0.777s. A better segmentation effect was obtained on the basis of correct localization results, with an average time of 0.295 s. Therefore, it can be said that the video disk localization and segmentation algorithm studied in this paper has the advantages of low complexity, high speed, high accuracy and so on. Compared with other methods, it is more suitable for real time processing of real time system.
【學(xué)位授予單位】：沈陽工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41
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