会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 92. 发明申请
    • METHODS AND APPARATUS FOR SIMULTANEOUSLY INSPECTING MULTIPLE ARRAY REGIONS HAVING DIFFERENT PITCHES
    • 同时检查具有不同切片的多个阵列区域的方法和装置
    • US20110164130A1
    • 2011-07-07
    • US13062934
    • 2010-06-18
    • Hong ChenJason Z. Lin
    • Hong ChenJason Z. Lin
    • H04N7/18G01N23/00
    • G01N21/956G01N2021/95676G03F1/84H01L22/12
    • One embodiment relates to a method of automatically inspecting multiple array regions (102) simultaneously using an imaging apparatus (302). The method includes selecting (211 or 212) an optimal pixel size such that each array region in the multiple array regions has a grouped cell which is an integer number of pixels in size, and adjusting a pixel size of the imaging apparatus to be the selected optimal pixel size. Optimal pixel sizes within an available range of pixel sizes may be determined by finding (202) a largest common divider of cell sizes of the multiple array regions when the cell sizes are expressed in integers. Pre-set criteria may be applied to determine (208) which, if any, of the optimal pixel sizes are acceptable based on pre-set criteria. If none of the optimal pixel sizes are acceptable, then one of the array regions may be marked for digital interpolation (see 216). Other embodiments, aspects, and features are also disclosed.
    • 一个实施例涉及一种使用成像设备(302)同时自动检查多个阵列区域(102)的方法。 该方法包括:选择(211或212)最佳像素大小,使得多个阵列区域中的每个阵列区域具有分组的小区,其大小为整数像素,并且将成像设备的像素大小调整为所选择的 最佳像素大小。 可以通过在单元格大小以整数表示时,找到(202)多个阵列区域的单元大小的最大公共分频器来确定像素大小的可用范围内的最佳像素大小。 可以应用预设标准以基于预设标准来确定(208)哪些最佳像素大小是可接受的。 如果没有最佳像素大小是可以接受的,则可以将阵列区域之一标记为数字插值(参见216)。 还公开了其它实施例,方面和特征。
    • 94. 发明申请
    • Selection of Optimum Patterns in a Design Layout Based on Diffraction Signature Analysis
    • 基于衍射签名分析的设计布局中最优模式的选择
    • US20110107280A1
    • 2011-05-05
    • US12914954
    • 2010-10-28
    • Hua-Yu LiuLuoqi ChenHong ChenZhi-Pan Li
    • Hua-Yu LiuLuoqi ChenHong ChenZhi-Pan Li
    • G06F17/50
    • G06F17/5081G03F1/144G03F1/36G03F7/70125G03F7/70425G03F7/70441G03F7/705G03F7/70666G06F17/50G06F17/5009
    • The present invention relates generally to selecting optimum patterns based on diffraction signature analysis, and more particularly to, using the optimum patterns for mask-optimization for lithographic imaging. A respective diffraction map is generated for each of a plurality of target patterns from an initial larger set of target patterns from the design layout. Diffraction signatures are identified from the various diffraction maps. The plurality of target patterns is grouped into various diffraction-signature groups, the target patterns in a specific diffraction-signature group having similar diffraction signature. A subset of target patterns is selected to cover all possible diffraction-signature groups, such that the subset of target patterns represents at least a part of the design layout for the lithographic process. The grouping of the plurality of target patterns may be governed by predefined rules based on similarity of diffraction signature. The predefined rules comprise coverage relationships existing between the various diffraction-signature groups.
    • 本发明一般涉及基于衍射特征分析来选择最佳图案,更具体地说,涉及使用用于光刻成像的掩模优化的最佳图案。 从来自设计布局的初始较大的目标图案集合中的多个目标图案中的每一个生成相应的衍射图。 从各种衍射图识别衍射特征。 多个目标图案被分组成各种衍射签名组,具有相似衍射特征的特定衍射签名组中的目标图案。 选择目标图案的子集以覆盖所有可能的衍射签名组,使得目标图案的子集代表光刻工艺的设计布局的至少一部分。 多个目标图案的分组可以通过基于衍射签名的相似性的预定规则来管理。 预定义的规则包括存在于各种衍射签名组之间的覆盖关系。
    • 97. 发明授权
    • Automatic determination of joint space width from hand radiographs
    • 自动确定手部放射线照片的关节间隙宽度
    • US07668356B2
    • 2010-02-23
    • US11482445
    • 2006-07-07
    • Hong ChenCarol L. Novak
    • Hong ChenCarol L. Novak
    • G06K9/00
    • G06T7/60G06T7/0012G06T7/12G06T7/155G06T2207/10116G06T2207/20044G06T2207/30008Y10S128/922
    • A computer-implemented method for determining a joint space width includes providing image data for a skeleton, thresholding the image data, and performing a connected component analysis on thresholded image data. The method further includes extracting contours of the thresholded image data according to the connected component analysis, performing a skeletonization of the thresholded image data using a first fast marching analysis of the thresholded image data, locating at least one finger joint of skeletonized image data, extracting bone boundaries using a second fast marching analysis of gradient information of the image data inside a region of interest, which includes a finger joint of the at least one finger joint, determining the joint space width given extracted bone boundaries, and outputting the joint space width.
    • 用于确定联合空间宽度的计算机实现的方法包括提供骨架的图像数据,阈值化图像数据以及对阈值化图像数据执行连接分量分析。 该方法还包括根据连通分量分析提取阈值图像数据的轮廓,使用阈值图像数据的第一快速行进分析来执行阈值化图像数据的骨架化,定位骨架化图像数据的至少一个手指关节,提取 骨骼边界,其使用包括所述至少一个手指关节的手指关节的所述感兴趣区域内的图像数据的梯度信息的第二快速行进分析,确定给定提取的骨边界的关节空间宽度,以及输出所述关节间隙 。