眼底血管的健康状态对于研究各类眼科疾病具有重要的参考意义。为了帮助临床医疗人员对眼底微血管形态结构图像的分析来诊断疾病,文中提出了一种基于编码-解码(Encoder-Decoder)结构的U-net的眼底血管分割方法。首先,在模型训练之前对...眼底血管的健康状态对于研究各类眼科疾病具有重要的参考意义。为了帮助临床医疗人员对眼底微血管形态结构图像的分析来诊断疾病,文中提出了一种基于编码-解码(Encoder-Decoder)结构的U-net的眼底血管分割方法。首先,在模型训练之前对图像进行预处理,然后使用Leaky ReLU激活函数替换U-net ReLU,避免了神经元的死亡问题,同时使用Adam(Adaptive Moment Estimate)优化器代替梯度下降法优化学习策略,最后对血管分割的平均交并比进行计算评估。实验表明,优化后的模型的平均精度可达到93.29%,相比原算法提升了3.26%。展开更多
Optic disc(OD)detection is a main step while developing automated screening systems for diabetic retinopathy.We present a method to automatically locate and extract the OD in digital retinal fundus images.Based on the...Optic disc(OD)detection is a main step while developing automated screening systems for diabetic retinopathy.We present a method to automatically locate and extract the OD in digital retinal fundus images.Based on the property that main blood vessels gather in OD,the method starts with Otsu thresholding segmentation to obtain candidate regions of OD.Consequently,the main blood vessels which are segmented in H channel of color fundus images in Hue saturation value(HSV)space.Finally,a weighted vessels’direction matched filter is proposed to roughly match the direction of the main blood vessels to get the OD center which is used to pick the true OD out from the candidate regions of OD.The proposed method was evaluated on a dataset containing 100 fundus images of both normal and diseased retinas and the accuracy reaches 98%.Furthermore,the average time cost in processing an image is 1.3 s.Results suggest that the approach is reliable,and can efficiently detect OD from fundus images.展开更多
文摘眼底血管的健康状态对于研究各类眼科疾病具有重要的参考意义。为了帮助临床医疗人员对眼底微血管形态结构图像的分析来诊断疾病,文中提出了一种基于编码-解码(Encoder-Decoder)结构的U-net的眼底血管分割方法。首先,在模型训练之前对图像进行预处理,然后使用Leaky ReLU激活函数替换U-net ReLU,避免了神经元的死亡问题,同时使用Adam(Adaptive Moment Estimate)优化器代替梯度下降法优化学习策略,最后对血管分割的平均交并比进行计算评估。实验表明,优化后的模型的平均精度可达到93.29%,相比原算法提升了3.26%。
基金National High Technology Research and Development Program of China(863 Program)(No.2006AA020804)Fundamental Research Funds for the Central Universities,China(No.NJ20120007)+2 种基金Jiangsu Province Science and Technology Support Plan,China(No.BE2010652)Program Sponsored for Scientific Innovation Research of College Graduate in Jangsu Province,China(No.CXLX11_0218)Shanghai University Scientific Selection and Cultivation for Outstanding Young Teachers in Special Fund,China(No.ZZGCD15081)。
文摘Optic disc(OD)detection is a main step while developing automated screening systems for diabetic retinopathy.We present a method to automatically locate and extract the OD in digital retinal fundus images.Based on the property that main blood vessels gather in OD,the method starts with Otsu thresholding segmentation to obtain candidate regions of OD.Consequently,the main blood vessels which are segmented in H channel of color fundus images in Hue saturation value(HSV)space.Finally,a weighted vessels’direction matched filter is proposed to roughly match the direction of the main blood vessels to get the OD center which is used to pick the true OD out from the candidate regions of OD.The proposed method was evaluated on a dataset containing 100 fundus images of both normal and diseased retinas and the accuracy reaches 98%.Furthermore,the average time cost in processing an image is 1.3 s.Results suggest that the approach is reliable,and can efficiently detect OD from fundus images.
