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1. 发明申请

WO2015167585A1 MEAT ASSESSMENT DEVICE 审中-公开
标题翻译：肉类评估装置
公开(公告)号：WO2015167585A1
公开(公告)日：2015-11-05
申请号：PCT/US2014/036648
申请日：2014-05-02
申请人： EMPIRE TECHNOLOGY DEVELOPMENT LLC
发明人： COOKE, Cameron
IPC分类号： G01N33/12
CPC分类号： G01N23/046 , G01N33/12 , G06T7/0002 , G06T7/0004 , G06T7/45 , G06T11/60 , G06T15/00 , G06T2207/10081 , G06T2207/10116 , G06T2207/20021 , G06T2207/30128 , G06T2211/40
摘要： A method for assessing the quality of a piece of meat may be described. The method may include creating a plurality of cross-sectional images through a piece of meat. The method may additionally include performing image analysis on at least one of the images to determine the arrangement of fat and lean meat within the piece of meat. The arrangement may be indicative of the quality of the piece of meat.
摘要翻译：可以描述用于评估一块肉的质量的方法。该方法可以包括通过一块肉形成多个横截面图像。该方法可以另外包括对至少一个图像执行图像分析以确定肉块内的脂肪和瘦肉的排列。该布置可以指示该块肉的质量。

2. 发明申请

WO2015071579A1 PROCÉDÉ DE CARACTÉRISATION AUTOMATIQUE DE LA TEXTURE D'UNE IMAGE NUMÉRIQUE 审中-公开
标题翻译：自动表征数字图像纹理的方法
公开(公告)号：WO2015071579A1
公开(公告)日：2015-05-21
申请号：PCT/FR2014/052858
申请日：2014-11-07
申请人： UNIVERSITE D'AIX MARSEILLE , CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
发明人： RICHARD, Frédéric Joseph Pierre
IPC分类号： G06T7/40
CPC分类号： G06T7/48 , G06T7/45 , G06T2207/20012 , G06T2207/20021 , G06T2207/30068
摘要： L'invention concerne un procédé de caractérisation automatique de la texture d'une image numérique, comportant : - l'acquisition (30) d'une image numérique formée d'une pluralité de pixels; - la définition (40), au sein de l'image numérique acquise, d'une pluralité de fenêtres d'analyse différentes, chaque fenêtre étant formée de pixels de l'image numérique; - l'estimation (80), pour chaque fenêtre définie, d'un exposant de Hurst H i à partir des seuls pixels de cette fenêtre, où l'indice i identifie de façon unique la fenêtre d'analyse utilisée pour estimer l'exposant H i ; - le calcul (100, 100') d'une signature, sous la forme d'une seule valeur numérique, caractéristique de la texture de l'image numérique, en combinant les exposants H i estimés pour chaque fenêtre de l'image numérique.
摘要翻译：本发明涉及一种自动表征数字图像的纹理的方法，包括： - 由多个像素形成的数字图像的获取（30）; - 在所获取的数字图像内的多个不同分析窗口中的定义（40），每个窗口由数字图像的像素形成; - 仅仅基于该窗口的像素的Hurst指数H i的每个窗口的估计（80），其中索引i唯一地标识用于估计指数Hi的分析窗口; 通过组合为数字图像的每个窗口估计的指数H，以单数值的形式计算（100,100'）数字图像的纹理的特征。

3. 发明申请

WO2004044845A3 IMAGE ANALYSIS 审中-公开
标题翻译：图像分析
公开(公告)号：WO2004044845A3
公开(公告)日：2004-08-26
申请号：PCT/GB0304841
申请日：2003-11-10
申请人： QINETIQ LTD , HADDON JOHN FRANCIS , WATSON SHARON KATRINA
发明人： HADDON JOHN FRANCIS , WATSON SHARON KATRINA
IPC分类号： G06T5/00 , G06T7/00 , G06T7/40 , G06F19/00
CPC分类号： G06K9/0014 , G06K9/00147 , G06T7/0012 , G06T7/11 , G06T7/136 , G06T7/45 , G06T2207/10056 , G06T2207/10116 , G06T2207/30024 , G06T2207/30068 , G06T2207/30096
摘要： A method for the automated analysis of digital images, particularly for the purpose of assessing the presence and severity of cancer in breast tissue based on the relative proportions of tubule formations and epithelial cells identified in digital images of histological slides. The method includes the step of generating a property co-occurrence matrix (PCM) from some or all of the pixels in the image, using the properties of local mean and local standard deviation of intensity in neighbourhoods of the selected pixels, and segmenting the image by labelling the selected pixels as belonging to specified classes based upon analysis of the PCM. In this way relatively dark and substantially textured regions representing epithelial cells in the image can be distinguished from lighter and more uniform background regions. Other steps include identifying groups of pixels representing duct cells in the image based on intensity, shape and size criteria, dilating those pixels into surrounding groups labelled as epithelial cells by a dimension to correspond to an overall tubule formation, and calculating a metric based on the ratio of the number of duct pixels after such dilation to the total number of duct and epithelial pixels. Other uses for the method could include the analysis of mineral samples containing certain types of crystal formations.
摘要翻译：一种用于数字图像的自动分析的方法，特别是基于在组织学载玻片的数字图像中鉴定的小管形成和上皮细胞的相对比例来评估乳腺组织中癌症的存在和严重性的目的。该方法包括使用图像中的一些或全部像素产生属性共生矩阵（PCM）的步骤，使用所选像素的邻域中的强度的局部均值和局部标准偏差的属性，以及分割图像通过基于PCM的分析将所选择的像素标记为属于指定类。以这种方式，可以将表示图像中的上皮细胞的相对较暗和基本纹理的区域与较轻和更均匀的背景区域区分开。其他步骤包括基于强度，形状和尺寸标准来识别表示图像中的管道细胞的像素组，将标记为上皮细胞的周围组的尺寸扩大为对应于整个小管形成的尺寸，以及基于这种扩张后的管道像素数与管道和上皮像素的总数之比。该方法的其他用途可能包括含有某些类型晶体结构的矿物样品的分析。

4. 发明申请

WO2016148657A1 METHOD OF DETECTING FIBROUS TISSUE IN A BIOLOGICAL SPECIMEN USING CO-LOCALIZED IMAGES GENERATED BY SECOND HARMONIC GENERATION AND TWO PHOTON EMISSION 审中-公开
标题翻译：使用第二次谐波生成和两个光子发射产生的局部化图像在生物样本中检测纤维组织的方法
公开(公告)号：WO2016148657A1
公开(公告)日：2016-09-22
申请号：PCT/SG2016/050129
申请日：2016-03-18
申请人： HISTOINDEX PTE LTD
发明人： HO, Gideon , GOLE, Laurent , YU, Weimiao
IPC分类号： G01N21/63 , G02F1/35 , G01N21/64 , G06T5/00
CPC分类号： G01N21/6486 , G01N21/636 , G01N21/6458 , G01N33/4833 , G01N2021/6439 , G02F1/37 , G06K9/0014 , G06K9/469 , G06K9/6215 , G06T7/0012 , G06T7/45 , G06T2207/10064 , G06T2207/30024
摘要： The present disclosure offers a method of detecting the presence of fibrous tissue deposited to a biological specimen or tissue sample. Preferably, the method comprises the steps of illuminating the specimen using an electromagnetic radiation of an excitation wavelength that the specimen contains excitable materials or compound to result in auto-fluorescence emitting a first electromagnetic signal caused by two-photon excitation, the specimen contains non-linear materials to generate a second electromagnetic signal in the form of second harmonic wave pursuant to the illuminating step; recording the first and the second electromagnetic signals emitted from the specimen; co-localizing the recorded first and second electromagnetic signals to generate an image; and detecting presence of the fibrous tissue deposited to the specimen using the generated image. More preferably, the light source is a laser beam or the like operable to induce two-photon excitation in the given tissue sample.
摘要翻译：本公开提供了一种检测沉积到生物样本或组织样品上的纤维组织的存在的方法。优选地，该方法包括以下步骤：使用激发波长的电磁辐射来照射样本，所述激发波长的样本含有可兴奋材料或化合物，导致自发荧光发射由双光子激发引起的第一电磁信号，线性材料，以根据照明步骤产生二次谐波形式的第二电磁信号; 记录从样本发射的第一和第二电磁信号; 对记录的第一和第二电磁信号进行共定位以产生图像; 以及使用所生成的图像来检测沉积到样本上的纤维组织的存在。更优选地，光源是可操作以在给定组织样品中诱导双光子激发的激光束等。

5. 发明申请

WO2013025692A1 A METHOD AND SYSTEM OF CHARACTERIZATION OF CAROTID PLAQUE 审中-公开
标题翻译： CAROTID PLAQUE的表征方法与系统
公开(公告)号：WO2013025692A1
公开(公告)日：2013-02-21
申请号：PCT/US2012/050752
申请日：2012-08-14
申请人： VPDIAGNOSTICS, INC. , SUI, Lei
发明人： SUI, Lei
IPC分类号： A61B8/08 , A61B5/055 , G06T7/00
CPC分类号： G06K9/52 , A61B5/0035 , A61B5/055 , A61B8/06 , A61B8/0858 , A61B8/0891 , A61B8/14 , A61B8/488 , A61B8/5223 , A61B8/5261 , A61B8/5284 , G06T7/11 , G06T7/45 , G06T2207/10132 , G06T2207/20081 , G06T2207/30101
摘要： A system and method of obtaining and analyzing ultrasound images of a patient provides for the identification of specific tissue types in using the image data. A feature vector set of sub-regions of the region of interest is obtained, dimensionally reduced and evaluated using a heuristic to identify the tissue type. Where the tissue type is suitable for image standardization, the overall gray scale of the image is adjusted with respect to a predetermined gray scale for the identified tissue type. The image may be segmented and plaque regions identified and characterized. The characterized plaque and other parameters such as percent stenosis may be used to determine a risk score for the patient.
摘要翻译：获得和分析患者的超声图像的系统和方法提供了在使用图像数据时识别特定组织类型。获得感兴趣区域的子区域的特征向量集，使用启发式进行尺寸缩小和评估以识别组织类型。在组织类型适合于图像标准化的情况下，针对所识别的组织类型，相对于预定灰度调整图像的总体灰度。图像可以被分割并且斑块区域被识别和表征。特征性斑块和其他参数如狭窄百分比可用于确定患者的风险评分。

6. 发明申请

WO2019049324A1 IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD AND STORAGE MEDIUM 审中-公开
公开(公告)号：WO2019049324A1
公开(公告)日：2019-03-14
申请号：PCT/JP2017/032530
申请日：2017-09-08
申请人： NEC CORPORATION
发明人： NAGARE Madhuri Mahendra , AOKI Hirofumi , SAGI Kazutoshi
IPC分类号： G06T1/00 , G06T7/00
CPC分类号： G06T5/008 , G06T7/12 , G06T7/45 , G06T2207/10036 , G06T2207/20076 , G06T2207/20081 , G06T2207/20084
摘要： An image processing device 300 which is capable of accurately detect pixels covered by cloud shadows and remove effects of the cloud shadows in an images are provided. The image processing device 300 for detection and correction of influence caused by one or more clouds includes: a cloud transmittance calculation unit 31 that calculates transmittance of the one or more clouds in an input image, for each pixel; a cloud height estimation unit 32 that determines estimation of a height from the ground to each cloud in the input image for the each pixel to detect position of corresponding one or more shadows; an attenuation factor estimation unit 33 that calculates attenuation factors for the direct sun irradiance by applying an averaging filter to the cloud transmittance calculated, for the each pixel; and a shadow removal unit 34 that corrects pixels affected by the one or more shadows, based on a physical model of a cloud shadow formation by employing the attenuation factors calculated and the position, and outputs an image which includes the pixels corrected.

7. 发明申请

WO2014080305A2 INTEGRATED PHENOTYPING EMPLOYING IMAGE TEXTURE FEATURES. 审中-公开
标题翻译：集成的相机采用图像纹理特征。
公开(公告)号：WO2014080305A2
公开(公告)日：2014-05-30
申请号：PCT/IB2013059663
申请日：2013-10-25
申请人： KONINKL PHILIPS NV
发明人： BANERJEE NILANJANA , DIMITROVA NEVENKA , VARADAN VINAY , KAMALAKARAN SITHARTHAN , JANEVSKI ANGEL , MAITY SAYAN
IPC分类号： G06T7/40
CPC分类号： G06T7/45 , G06K9/6267 , G06T2207/10088 , G06T2207/30068
摘要： Image texture feature values are computed for a set of image texture features from an image of an anatomical feature of interest in a subject, and the subject is classified respective to a molecular feature of interest based on the computed image texture feature values. The image texture feature values may be computed from one or more gray level co-occurrence matrices (GLCMs), and the image texture features may include Haralick and/or Tamura image texture features. To train the classifier, reference image texture feature values are computed for at least the set of image texture features from images of the anatomical feature of interest in reference subjects. The reference image texture feature values are divided into different population groups representing different values of the molecular feature of interest, and the classifier is trained to distinguish between the different population groups based on the reference image texture feature values.
摘要翻译：根据受试者感兴趣的解剖学特征的图像，针对一组图像纹理特征计算图像纹理特征值，并且基于所计算的图像纹理特征值将对象分类为感兴趣的分子特征。可以从一个或多个灰度共生矩阵（GLCM）计算图像纹理特征值，并且图像纹理特征可以包括Haralick和/或Tamura图像纹理特征。为了训练分类器，参考图像纹理特征值是从参考对象中感兴趣的解剖特征的图像中计算至少一组图像纹理特征。将参考图像纹理特征值分成表示不同分子特征值的不同群体组，并且根据参考图像纹理特征值对分类器进行训练以区分不同群体组。

8. 发明申请

WO2010014826A2 APPARATUS AND METHOD FOR GENERATING FORMATION TEXTURAL FEATURE IMAGES 审中-公开
标题翻译：用于生成纹理特征图像的装置和方法
公开(公告)号：WO2010014826A2
公开(公告)日：2010-02-04
申请号：PCT/US2009/052276
申请日：2009-07-30
申请人： BAKER HUGHES INCORPORATED , PADMAKER, Deo
发明人： PADMAKER, Deo
IPC分类号： E21B47/02 , E21B47/04 , E21B47/12
CPC分类号： E21B47/0002 , G01V11/00 , G01V2210/6163 , G06T7/45 , G06T11/00
摘要： Apparatus and methods for providing an image of a formation textural feature are disclosed, which in one aspect may include defining a plurality of sectors for a wellbore, obtaining wellbore image data corresponding to each sector over a wellbore depth, obtaining a gray level co-occurrence matrix from the wellbore image data for a selected textural feature of the formation, and generating from the gray scale co-occurrence matrix an image of the selected textural feature over the wellbore depth.
摘要翻译：公开了用于提供地层纹理特征的图像的设备和方法，其在一个方面可以包括为井眼定义多个扇区，获得对应于井筒深度上的每个扇区的井筒图像数据，获得灰度级同现从所述井眼图像数据获取所述地层的选定纹理特征的矩阵，以及从所述灰度共生矩阵生成所述选定纹理特征在所述井眼深度上的图像。

9. 发明申请

WO2016067254A1 TEXTURE ANALYSIS MAP FOR IMAGE DATA 审中-公开
标题翻译：图像数据的纹理分析图
公开(公告)号：WO2016067254A1
公开(公告)日：2016-05-06
申请号：PCT/IB2015/058382
申请日：2015-10-30
申请人： KONINKLIJKE PHILIPS N.V.
发明人： CARMI, Raz
IPC分类号： G06T7/40
CPC分类号： G06T7/45 , G06K9/4642 , G06T11/008 , G06T2207/10081
摘要： A method includes obtaining at least a first energy dependent spectral image volume and a second different energy dependent spectral image volume from reconstructed spectral image data. The method further includes generating a multi-dimensional spectral diagram that maps, for each voxel, a value of the first energy dependent spectral image volume to a corresponding value of the second energy dependent spectral image volume. The method further includes generating a set of spectral texture analysis weights from the multi-dimensional spectral diagram. The method further includes retrieving a set of texture analysis functions, which are generated as a function of voxel intensity and voxel gradient value from a co-occurrence matrix histogram. The method further includes generating a texture analysis map through a texture analysis of the reconstructed spectral image data with the set of texture analysis functions and the set of spectral texture analysis weights and visually presenting the texture analysis map.
摘要翻译：一种方法包括从重构的光谱图像数据获得至少第一能量依赖光谱图像体积和第二不同的能量相关光谱图像体积。该方法还包括生成多维光谱图，其为每个体素将第一能量相关光谱图像体积的值映射到第二能量依赖光谱图像体积的对应值。该方法还包括从多维谱图生成一组光谱纹理分析权重。该方法还包括从共现矩阵直方图中检索作为体素强度和体素梯度值的函数产生的一组纹理分析函数。该方法还包括通过纹理分析功能和一组光谱纹理分析权重的组合分析重建光谱图像数据的纹理分析，并可视化呈现纹理分析图，生成纹理分析图。

10. 发明申请

WO2012016242A2 SYSTEMS AND METHODS FOR SEGMENTATION AND PROCESSING OF TISSUE IMAGES AND FEATURE EXTRACTION FROM SAME FOR TREATING, DIAGNOSING, OR PREDICTING MEDICAL CONDITIONS 审中-公开
标题翻译：用于组织和加工组织图像的系统和方法以及用于治疗，诊断或预测医疗条件的特征提取
公开(公告)号：WO2012016242A2
公开(公告)日：2012-02-02
申请号：PCT/US2011046149
申请日：2011-08-01
申请人： AUREON BIOSCIENCES INC , AJEMBA PETER , SCOTT RICHARD , RAMACHANDRAN JANAKIRAMANAN , ZEINEH JACK , DONOVAN MICHAEL , AL-KOFAHI YOUSEF , FERNANDEZ GERARDO , SAPIR MARINA , LIU QIUHUA , KHAN FAISAL
发明人： AJEMBA PETER , SCOTT RICHARD , RAMACHANDRAN JANAKIRAMANAN , ZEINEH JACK , DONOVAN MICHAEL , AL-KOFAHI YOUSEF , FERNANDEZ GERARDO , SAPIR MARINA , LIU QIUHUA , KHAN FAISAL
IPC分类号： G06T5/30
CPC分类号： G06K9/00147 , G06T5/008 , G06T7/0012 , G06T7/11 , G06T7/155 , G06T7/45 , G06T2207/10056 , G06T2207/20041 , G06T2207/20212 , G06T2207/30024
摘要： Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.
摘要翻译：提供装置，方法和计算机可读介质用于分组，处理（例如，预处理和/或后处理）和/或从诸如例如核和/或细胞质的图像的组织图像的特征提取。可以通过苏木精和曙红（H＆E）染色，免疫荧光（IF）检测，免疫组织化学（IHC），类似和/或相关的染色过程和/或其它过程产生由本文描述的各种实施方案处理的组织图像。本文所述的预测特征可以被提供用于例如用于治疗，诊断和/或预测一种或多种医学病症（例如癌症或其他）的发生（例如复发）的一种或多种预测模型疾病类型

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