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    OBTAINING DATA FOR AUTOMATIC GLAUCOMA SCREENING, AND SCREENING AND DIAGNOSTIC TECHNIQUES AND SYSTEMS USING THE DATA
    1.
    发明申请
    OBTAINING DATA FOR AUTOMATIC GLAUCOMA SCREENING, AND SCREENING AND DIAGNOSTIC TECHNIQUES AND SYSTEMS USING THE DATA 有权
    获取用于自动GLAUCOMA筛选的数据，以及使用数据的筛选和诊断技术和系统

    公开(公告)号：US20120230564A1

    公开(公告)日：2012-09-13

    申请号：US13510290

    申请日：2010-11-16

    申请人： Jiang Liu ,  Zhuo Zhang ,  Wing Kee Damon Wong ,  Ngan Meng Tan ,  Fengshou Yin ,  Beng Hai Lee ,  Huiqi Li ,  Joo Hwee Lim ,  Carol Cheung ,  Tin Aung ,  Tien Yin Wong ,  Ziyang Liang ,  Jun Cheng ,  Baskaran Mani

    发明人： Jiang Liu ,  Zhuo Zhang ,  Wing Kee Damon Wong ,  Ngan Meng Tan ,  Fengshou Yin ,  Beng Hai Lee ,  Huiqi Li ,  Joo Hwee Lim ,  Carol Cheung ,  Tin Aung ,  Tien Yin Wong ,  Ziyang Liang ,  Jun Cheng ,  Baskaran Mani

    IPC分类号： G06K9/46

    CPC分类号： A61B3/0025 ,  A61B3/12 ,  A61B5/02007 ,  A61B5/7264 ,  A61B5/7267 ,  A61B5/7275 ,  G06T7/0012 ,  G06T7/40 ,  G06T2207/30041

    摘要： A non-stereo fundus image is used to obtain a plurality of glaucoma indicators. Additionally, genome data for the subject is used to obtain genetic marker data relating to one or more genes and/or SNPs associated with glaucoma. The glaucoma indicators indicators and genetic marker data are input into an adaptive model operative to generate an output indicative of a risk of glaucoma in the subject. In combination, the genetic indicators and genome data are more informative about the risk of glaucoma than either of the two in isolation. The adaptive model may be a two-stage model, having a first stage in which individual genetic indicators are combined with respective portions of the genome data by first adaptive model modules to form respective first outputs, and a second stage in which the first outputs are combined by a second adaptive mode. Texture analysis is performed on the fundus images to classify them based on their quality, and only images which are determined to meet a quality criterion are subjected to an analysis to determine if they exhibit glaucoma indicators. Also, the images are put into a standard format. The system may include estimating the position of the optic cup by combining results from multiple optic cup segmentation techniques. The system may include estimating the position of the optic disc by applying edge detection to the funds image, excluding edge points that are unlikely to be optic disc boundary points, and estimating the position of an optic disc by fitting an ellipse to the remaining edge points.

    摘要翻译： 使用非立体眼底图像来获得多个青光眼指示符。 此外，用于受试者的基因组数据用于获得与与青光眼相关的一个或多个基因和/或SNP相关的遗传标记数据。 青光眼指标指标和遗传标记数据被输入到适应模型中，该模型用于产生指示受试者青光眼风险的输出。 综合来看，遗传指标和基因组数据对于青光眼的风险比孤立的两者之一更有信息。 自适应模型可以是两阶段模型，其具有第一阶段，其中通过第一自适应模型模块将个体遗传指标与基因组数据的相应部分组合以形成相应的第一输出，第二阶段中，第一输出是 通过第二自适应模式组合。 对眼底图像进行纹理分析，根据其质量对其进行分类，仅对满足质量标准的图像进行分析，以确定其是否呈现青光眼指标。 此外，图像被放入标准格式。 该系统可以包括通过组合来自多个光学杯分割技术的结果来估计光学杯的位置。 该系统可以包括通过对资金图像应用边缘检测来估计视盘的位置，不包括不太可能是视盘边界点的边缘点，以及通过将椭圆拟合到剩余边缘点来估计视盘的位置 。

    Obtaining data for automatic glaucoma screening, and screening and diagnostic techniques and systems using the data
    2.
    发明授权
    Obtaining data for automatic glaucoma screening, and screening and diagnostic techniques and systems using the data 有权
    获取自动青光眼筛查数据，以及使用数据的筛选和诊断技术和系统

    公开(公告)号：US09107617B2

    公开(公告)日：2015-08-18

    申请号：US13510290

    申请日：2010-11-16

    申请人： Jiang Liu ,  Zhuo Zhang ,  Wing Kee Damon Wong ,  Ngan Meng Tan ,  Fengshou Yin ,  Beng Hai Lee ,  Huiqi Li ,  Joo Hwee Lim ,  Carol Cheung ,  Tin Aung ,  Tien Yin Wong ,  Ziyang Liang ,  Jun Cheng ,  Baskaran Mani

    发明人： Jiang Liu ,  Zhuo Zhang ,  Wing Kee Damon Wong ,  Ngan Meng Tan ,  Fengshou Yin ,  Beng Hai Lee ,  Huiqi Li ,  Joo Hwee Lim ,  Carol Cheung ,  Tin Aung ,  Tien Yin Wong ,  Ziyang Liang ,  Jun Cheng ,  Baskaran Mani

    IPC分类号： A61B3/12 ,  A61B5/02 ,  A61B5/00

    CPC分类号： A61B3/0025 ,  A61B3/12 ,  A61B5/02007 ,  A61B5/7264 ,  A61B5/7267 ,  A61B5/7275 ,  G06T7/0012 ,  G06T7/40 ,  G06T2207/30041

    摘要： A non-stereo fundus image is used to obtain a plurality of glaucoma indicators. Additionally, genome data for the subject is used to obtain genetic marker data relating to one or more genes and/or SNPs associated with glaucoma. The glaucoma indicators and genetic marker data are input into an adaptive model operative to generate an output indicative of a risk of glaucoma in the subject. In combination, the genetic indicators and genome data are more informative about the risk of glaucoma than either of the two in isolation. The adaptive model may be a two-stage model, having a first stage in which individual genetic indicators are combined with respective portions of the genome data by first adaptive model modules to form respective first outputs, and a second stage in which the first outputs are combined by a second adaptive mode. Texture analysis is performed on the fundus images to classify them based on their quality, and only images which are determined to meet a quality criterion are subjected to an analysis to determine if they exhibit glaucoma indicators. Also, the images are put into a standard format. The system may include estimating the position of the optic cup by combining results from multiple optic cup segmentation techniques. The system may include estimating the position of the optic disc by applying edge detection to the funds image, excluding edge points that are unlikely to be optic disc boundary points, and estimating the position of an optic disc by fitting an ellipse to the remaining edge points.

    摘要翻译： 使用非立体眼底图像来获得多个青光眼指示符。 此外，用于受试者的基因组数据用于获得与与青光眼相关的一个或多个基因和/或SNP相关的遗传标记数据。 青光眼指标和遗传标记数据被输入到适应模型中，该模型用于产生指示受试者青光眼风险的输出。 综合来看，遗传指标和基因组数据对于青光眼的风险比孤立的两者之一更有信息。 自适应模型可以是两阶段模型，其具有第一阶段，其中通过第一自适应模型模块将个体遗传指标与基因组数据的相应部分组合以形成相应的第一输出，第二阶段中，第一输出是 通过第二自适应模式组合。 对眼底图像进行纹理分析，根据其质量对其进行分类，仅对满足质量标准的图像进行分析，以确定其是否呈现青光眼指标。 此外，图像被放入标准格式。 该系统可以包括通过组合来自多个光学杯分割技术的结果来估计光学杯的位置。 该系统可以包括通过对资金图像应用边缘检测来估计视盘的位置，排除不太可能是视盘边界点的边缘点，以及通过将椭圆拟合到剩余边缘点来估计视盘的位置 。

    AUTOMATIC OPACITY DETECTION SYSTEM FOR CORTICAL CATARACT DIAGNOSIS
    8.
    发明申请
    AUTOMATIC OPACITY DETECTION SYSTEM FOR CORTICAL CATARACT DIAGNOSIS 审中-公开
    用于CORTICAL CATARACT诊断的自动消隐检测系统

    公开(公告)号：US20110091084A1

    公开(公告)日：2011-04-21

    申请号：US12993751

    申请日：2008-05-20

    申请人： Huiqi Li ,  Joo Hwee Lim ,  Jiang Liu ,  Li Liang Ko ,  Wing Kee Damon Wong ,  Tien Yin Wong

    发明人： Huiqi Li ,  Joo Hwee Lim ,  Jiang Liu ,  Li Liang Ko ,  Wing Kee Damon Wong ,  Tien Yin Wong

    IPC分类号： G06K9/00

    CPC分类号： G06T7/0012 ,  G06T7/44 ,  G06T7/60 ,  G06T2207/20104 ,  G06T2207/30041

    摘要： A method performed by a computer system for detecting opacity in an image of the lens of an eye. The method includes detecting a region of interest in a picture of the lens, and processing the region of interest to produce a modified image using an algorithm which emphasizes opacity associated with a cortical cataract relative to opacity caused by other types of opacity, such as opacity caused by posterior sub-capsular cataracts (PSC). The modified image may be used for grading the level of cortical opacity, by measuring, in the modified image, the proportion of opacity in at least one area of the region of interest.

    摘要翻译： 一种由计算机系统执行的用于检测眼睛透镜的图像中的不透明度的方法。 该方法包括检测透镜的图片中的感兴趣区域，以及使用强调与皮质性白内障相关的不透明度的算法来处理感兴趣区域以产生相对于由其他类型的不透明度引起的不透明度的算法，诸如不透明度 由后囊性白内障（PSC）引起。 经修改的图像可以用于通过在修改图像中测量感兴趣区域的至少一个区域中的不透明度的比例来评估皮层不透明度的水平。