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1.发明申请Real-time implementation of field programmable gate arrays (FPGA) design in hyperspectral imaging 失效在高光谱成像中实时实现现场可编程门阵列（FPGA）设计公开(公告)号：US20050015418A1
公开(公告)日：2005-01-20
申请号：US10875102
申请日：2004-06-24
Applicant: Chein-I Chang , Jianwei Wang
Inventor： Chein-I Chang , Jianwei Wang
CPC classification number: G06K9/00986 , G06F7/5446 , G06F17/11 , G06K9/0063 , G06T7/11 , G06T7/194 , G06T2200/28 , G06T2207/10036 , G06T2207/30212
Abstract: A Field Programmable Gate Arrays (FPGA) design uses a Coordinate Rotation DIgital Computer (CORDIC) algorithm that can convert a Givens rotation of a vector to a set of shift-add operations. The CORDIC algorithm can be easily implemented in hardware architecture, therefore in FPGA. Since the computation of the inverse of the data correlation matrix involves a series of Givens rotations, the utility of the CORDIC algorithm allows a causal Constrained Energy Minimization (CEM) to perform real-time processing in FPGA. An FPGA implementation of the causal CEM is described and its detailed architecture is also described.
Abstract translation: 现场可编程门阵列（FPGA）设计使用坐标旋转二进制计算机（CORDIC）算法，可将矢量的Givens旋转转换为一组移位加法运算。 CORDIC算法可以在硬件体系结构中轻松实现，因此可以在FPGA中实现。 由于数据相关矩阵的逆的计算涉及一系列Givens旋转，因此CORDIC算法的实用性允许因果约束能量最小化（CEM）在FPGA中执行实时处理。 描述了因果CEM的FPGA实现，并对其详细架构进行了描述。
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公开(公告)号：US20090046908A1
公开(公告)日：2009-02-19
申请号：US12190584
申请日：2008-08-12
Applicant: Nabile Safdar , Bharath Ramakrishna , Chein-I Chang , Wei-min Liu , Khan Siddiqui , Eliot Siegel
Inventor： Nabile Safdar , Bharath Ramakrishna , Chein-I Chang , Wei-min Liu , Khan Siddiqui , Eliot Siegel
IPC: A61B5/00
CPC classification number: A61B5/103 , A61B5/055 , A61B5/4514 , A61B5/4528 , A61B6/03 , G06T7/0012 , G06T7/11 , G06T7/136 , G06T2200/24 , G06T2207/10081 , G06T2207/10088 , G06T2207/20132 , G06T2207/30004
Abstract: Techniques for automatically detecting meniscus include receiving pixels from a scanning device directed to a knee of a subject. Also received is a region of interest that includes pixels that correspond to at least a portion of a meniscus of the knee. Without human intervention, a meniscus extraction threshold is determined based on pixel intensities in the region of interest. A meniscus object portion of the scan data is further determined without human intervention based on the meniscus extraction threshold and a geometrical constraint.Other techniques for automatically detecting meniscal tears includes receiving a meniscus object portion of scan data from a scanning device and receiving threshold data that indicates a meniscus extraction threshold. Without human intervention, a propensity for meniscal tears is determined based on the threshold data and the meniscus object portion of the scan data.
Abstract translation: 用于自动检测弯液面的技术包括从指向对象的膝盖的扫描装置接收像素。 还接收的是包括对应于膝盖的弯液面的至少一部分的像素的感兴趣区域。 在没有人为干预的情况下，基于感兴趣区域中的像素强度来确定弯液面提取阈值。 基于弯月面提取阈值和几何约束，进一步确定扫描数据的弯液面物体部分，而无需人为干预。 用于自动检测半月板眼泪的其它技术包括从扫描装置接收扫描数据的弯月面物体部分，以及接收指示弯月面提取阈值的阈值数据。 在没有人为干预的情况下，根据扫描数据的阈值数据和弯月面对象部分来确定半月板撕裂的倾向。
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公开(公告)号：US5784485A
公开(公告)日：1998-07-21
申请号：US296039
申请日：1994-08-25
Applicant: Youguang Xu , Chein-I Chang
Inventor： Youguang Xu , Chein-I Chang
CPC classification number: G06K9/4628 , G06K2209/01
Abstract: The present invention relates to a new and useful Automated Pattern Recognition Device comprising a neural-network system, implemented on a general purpose computer, and capable of recognizing not only printed characters but also handwritten characters and other patterns in n-dimensions. The system incorporates novel feature extraction which generates an additional dimension from an n-dimensional input pattern, for example, a three-dimensional feature pattern from a two dimensional input pattern, resulting in shift-invariance, scale-invariance, and invariance to slight rotation.
Abstract translation: 本发明涉及一种新的和有用的自动模式识别装置，其包括在通用计算机上实现的神经网络系统，并且能够识别不仅印刷字符，而且能够识别n维的手写字符和其他图案。 该系统包含新的特征提取，其从n维输入模式生成附加尺寸，例如来自二维输入图案的三维特征图案，导致偏移不变性，尺度不变性和不变性以进行轻微旋转 。
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公开(公告)号：US08798171B2
公开(公告)日：2014-08-05
申请号：US12824498
申请日：2010-06-28
Applicant: Chein-I Chang , Han-Jieh Chang , Yang-Lang Chang
Inventor： Chein-I Chang , Han-Jieh Chang , Yang-Lang Chang
CPC classification number: H04N19/59 , H04N19/132 , H04N19/172 , H04N19/182 , H04N19/186 , H04N19/30 , H04N19/587
Abstract: Techniques are provided herein for receiving at a video processing device color video frames comprising grayscale components and color components. The grayscale components corresponding to each of the color video frames are extracted as each of the color video frames is received to obtain grayscale video frames. The grayscale video frames are transmitted at a first transmission rate. Color components for selected color video frames are periodically fused with selected grayscale video frames to obtain fused color video frames, and the fused color video frames are transmitted at a second transmission rate interspersed with the grayscale video frames transmitted at the first transmission rate.
Abstract translation: 本文提供了用于在视频处理设备处接收包括灰度分量和颜色分量的彩色视频帧的技术。 随着每个彩色视频帧被接收以获得灰度视频帧，提取对应于每个彩色视频帧的灰度分量。 以第一传输速率发送灰度视频帧。 所选择的彩色视频帧的颜色分量与所选择的灰度视频帧周期性地融合，以获得融合的彩色视频帧，并且融合的彩色视频帧以散布有以第一传输速率传输的灰度视频帧的第二传输速率传输。
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公开(公告)号：US08180126B2
公开(公告)日：2012-05-15
申请号：US12190584
申请日：2008-08-12
Applicant: Nabile Safdar , Bharath Ramakrishna , Chein-I Chang , Wei-min Liu , Khan Siddiqui , Eliot Siegel
Inventor： Nabile Safdar , Bharath Ramakrishna , Chein-I Chang , Wei-min Liu , Khan Siddiqui , Eliot Siegel
IPC: G06K9/00
CPC classification number: A61B5/103 , A61B5/055 , A61B5/4514 , A61B5/4528 , A61B6/03 , G06T7/0012 , G06T7/11 , G06T7/136 , G06T2200/24 , G06T2207/10081 , G06T2207/10088 , G06T2207/20132 , G06T2207/30004
Abstract: Techniques for automatically detecting meniscus include receiving pixels from a scanning device directed to a knee of a subject. Also received is a region of interest that includes pixels that correspond to at least a portion of a meniscus of the knee. Without human intervention, a meniscus extraction threshold is determined based on pixel intensities in the region of interest. A meniscus object portion of the scan data is further determined without human intervention based on the meniscus extraction threshold and a geometrical constraint. Other techniques for automatically detecting meniscal tears includes receiving a meniscus object portion of scan data from a scanning device and receiving threshold data that indicates a meniscus extraction threshold. Without human intervention, a propensity for meniscal tears is determined based on the threshold data and the meniscus object portion of the scan data.
Abstract translation: 用于自动检测弯液面的技术包括从指向对象的膝盖的扫描装置接收像素。 还接收的是包括对应于膝盖的弯液面的至少一部分的像素的感兴趣区域。 在没有人为干预的情况下，基于感兴趣区域中的像素强度来确定弯液面提取阈值。 基于弯月面提取阈值和几何约束，进一步确定扫描数据的弯液面物体部分，而无需人为干预。 用于自动检测半月板眼泪的其它技术包括从扫描装置接收扫描数据的弯月面物体部分，以及接收指示弯月面提取阈值的阈值数据。 在没有人为干预的情况下，根据扫描数据的阈值数据和弯月面对象部分来确定半月板撕裂的倾向。
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Patent Agency Ranking
6.发明授权Real-time implementation of field programmable gate arrays (FPGA) design in hyperspectral imaging 失效在高光谱成像中实时实现现场可编程门阵列（FPGA）设计公开(公告)号：US07366326B2
公开(公告)日：2008-04-29
申请号：US10875102
申请日：2004-06-24
Applicant: Chein-I Chang , Jianwei Wang
Inventor： Chein-I Chang , Jianwei Wang
IPC: G06K9/00
CPC classification number: G06K9/00986 , G06F7/5446 , G06F17/11 , G06K9/0063 , G06T7/11 , G06T7/194 , G06T2200/28 , G06T2207/10036 , G06T2207/30212
Abstract: A Field Programmable Gate Arrays (FPGA) design uses a Coordinate Rotation DIgital Computer (CORDIC) algorithm that can convert a Givens rotation of a vector to a set of shift-add operations. The CORDIC algorithm can be easily implemented in hardware architecture, therefore in FPGA. Since the computation of the inverse of the data correlation matrix involves a series of Givens rotations, the utility of the CORDIC algorithm allows a causal Constrained Energy Minimization (CEM) to perform real-time processing in FPGA. An FPGA implementation of the causal CEM is described and its detailed architecture is also described.
Abstract translation: 现场可编程门阵列（FPGA）设计使用坐标旋转二进制计算机（CORDIC）算法，可将矢量的Givens旋转转换为一组移位加法运算。 CORDIC算法可以在硬件体系结构中轻松实现，因此可以在FPGA中实现。 由于数据相关矩阵的逆的计算涉及一系列Givens旋转，因此CORDIC算法的实用性允许因果约束能量最小化（CEM）在FPGA中执行实时处理。 描述了因果CEM的FPGA实现，并对其详细架构进行了描述。
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7.发明授权3-D localization of clustered microcalcifications using cranio-caudal and medio-lateral oblique view 有权使用颅尾和中外侧斜视图进行聚类微钙化的3-D定位公开(公告)号：US06614921B1
公开(公告)日：2003-09-02
申请号：US09553725
申请日：2000-04-20
Applicant: Pau-Choo Chung , Chien-Shun Lo , Chein-I Chang , San-Kan Lee , Ching-Wen Yang
Inventor： Pau-Choo Chung , Chien-Shun Lo , Chein-I Chang , San-Kan Lee , Ching-Wen Yang
IPC: G06K900
CPC classification number: G06T7/0012 , Y10S128/915
Abstract: A method using CC and MLO views localized in a display in 3-D as a breast virtual model, incorporating, feature capturing using gradient, energy and entropy codes, calibration classification according to features using binary decision trees, nipple detection, and 3-D spatial coordinate transformation and display of breast clustered microcalcifications.
Abstract translation: 使用定位在3-D显示器中的CC和MLO视图作为乳房虚拟模型的方法，结合使用梯度，能量和熵码的特征捕获，根据使用二进制决策树的特征的校准分类，乳头检测和3-D 乳房聚类微钙化的空间坐标变换和显示。
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公开(公告)号：US08417748B2
公开(公告)日：2013-04-09
申请号：US12286443
申请日：2008-09-29
Applicant: Chein-I Chang
Inventor： Chein-I Chang
IPC: G06F7/00
CPC classification number: G06K9/0063
Abstract: Provided herein are algorithms and processes to extract endmembers from hyperspectral image data in real time. A Simplex Growing Algorithm is effective to estimate a p number of endmembers to be generated, to select one or more initial endmembers as a simplex of k members and to add a k+1 endmember to the simplex that yields a maximum simplex volume until k=p, thereby extracting one or more endmembers from the data. Alternatively, N-FINDR algorithms form an initial simplex set of p endmembers obtained from the hyperspectral image data, find a maximum volume of one or more initial p endmembers therewithin, replace one or more of the p endmembers within the simplex with one or more of the found p endmembers of maximum volume, and refind a maximum volume of p endmember(s) and replace p endmember(s) until no increase in p endmember(s) volume is found.
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公开(公告)号：US20110317073A1
公开(公告)日：2011-12-29
申请号：US12824498
申请日：2010-06-28
Applicant: Chein-I Chang , Han-Jieh Chang , Yang-Lang Chang
Inventor： Chein-I Chang , Han-Jieh Chang , Yang-Lang Chang
IPC: H04N9/65
CPC classification number: H04N19/59 , H04N19/132 , H04N19/172 , H04N19/182 , H04N19/186 , H04N19/30 , H04N19/587
Abstract: Techniques are provided herein for receiving at a video processing device color video frames comprising grayscale components and color components. The grayscale components corresponding to each of the color video frames are extracted as each of the color video frames is received to obtain grayscale video frames. The grayscale video frames are transmitted at a first transmission rate. Color components for selected color video frames are periodically fused with selected grayscale video frames to obtain fused color video frames, and the fused color video frames are transmitted at a second transmission rate interspersed with the grayscale video frames transmitted at the first transmission rate.
Abstract translation: 本文提供了用于在视频处理设备处接收包括灰度分量和颜色分量的彩色视频帧的技术。 随着每个彩色视频帧被接收以获得灰度视频帧，提取对应于每个彩色视频帧的灰度分量。 以第一传输速率发送灰度视频帧。 所选择的彩色视频帧的颜色分量与所选择的灰度视频帧周期性地融合，以获得融合的彩色视频帧，并且融合的彩色视频帧以散布有以第一传输速率传输的灰度视频帧的第二传输速率传输。
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公开(公告)号：US20090144350A1
公开(公告)日：2009-06-04
申请号：US12286443
申请日：2008-09-29
Applicant: Chein-I Chang
Inventor： Chein-I Chang
IPC: G06F15/00
CPC classification number: G06K9/0063
Abstract: Provided herein are algorithms and processes to extract endmembers from hyperspectral image data in real time. A Simplex Growing Algorithm is effective to estimate a p number of endmembers to be generated, to select one or more initial endmembers as a simplex of k members and to add a k+1 endmember to the simplex that yields a maximum simplex volume until k=p, thereby extracting one or more endmembers from the data. Alternatively, N-FINDR algorithms form an initial simplex set of p endmembers obtained from the hyperspectral image data, find a maximum volume of one or more initial p endmembers therewithin, replace one or more of the p endmembers within the simplex with one or more of the found p endmembers of maximum volume, and refind a maximum volume of p endmember(s) and replace p endmember(s) until no increase in p endmember(s) volume is found.
Abstract translation: 本文提供了从实时的高光谱图像数据中提取终端成员的算法和过程。 单生成长算法有效地估计待生成的终端成员的个数，选择一个或多个初始成员作为k个成员的单数，并将k + 1个终端添加到单纯形，直到k = p 从而从数据中提取一个或多个终端成员。 或者，N-FINDR算法形成从高光谱图像数据获得的p个终端成员的初始简单集合，在其中找到其中的一个或多个初始p个终端成员的最大容量，用单一形式中的一个或多个 找到最大量的最终成员，并修改最终量的最终成员，并替换p个成员，直到发现p个成员的体积没有增加。
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