公开(公告)号：US08086007B2

公开(公告)日：2011-12-27

申请号：US12286970

申请日：2008-10-03

申请人： Michelle Xiao-Hong Yan ,  Ti-chiun Chang ,  Markus Lendl ,  Stefan Boehm ,  Tong Fang ,  Peter Durlak

发明人： Michelle Xiao-Hong Yan ,  Ti-chiun Chang ,  Markus Lendl ,  Stefan Boehm ,  Tong Fang ,  Peter Durlak

IPC分类号： G06K9/00

CPC分类号： G06K9/4619 ,  G06K2209/05 ,  G06T7/0012

摘要： A method and system for image quality assessment is disclosed. The image quality assessment method is a no-reference method for objectively assessing the quality of medical images. This method is guided by the human vision model in order to accurately reflect human perception. A region of interest (ROI) of medical image is divided into non-overlapping blocks of equal size. Each of the blocks is categorized as a smooth block, a texture block, or an edge block. A perceptual sharpness measure, which is weighted by local contrast, is calculated for each of the edge blocks. A perceptual noise level measure, which is weighted by background luminance, is calculated for each of the smooth blocks. A sharpness quality index is determined based on the perceptual sharpness measures of all of the edge blocks, and a noise level quality index is determined based on the perceptual noise level measures of all of the smooth blocks. An overall image quality index can be determined by using task specific machine learning of samples of annotated images. The image quality assessment method can be used in applications, such as video/image compression and storage in healthcare and homeland security, and band-width limited wireless communication.

摘要翻译： 公开了一种用于图像质量评估的方法和系统。 图像质量评估方法是客观评估医学图像质量的非参考方法。 这种方法是以人类视觉模型为指导，以准确反映人类的感知。 医学图像的感兴趣区域（ROI）被划分成相等大小的不重叠块。 每个块被分类为平滑块，纹理块或边缘块。 针对每个边缘块计算出由局部对比度加权的感知锐度度量。 为每个平滑块计算感知噪声水平测量，其由背景亮度加权。 基于所有边缘块的感知锐度测量来确定锐度质量指标，并且基于所有平滑块的感知噪声水平测量来确定噪声水平质量指数。 可以通过使用注释图像的样本的任务特定机器学习来确定整体图像质量指数。 图像质量评估方法可用于医疗保健和国土安全中的视频/图像压缩和存储等应用，以及带宽有限的无线通信。

公开(公告)号：US20090116713A1

公开(公告)日：2009-05-07

申请号：US12286970

申请日：2008-10-03

申请人： Michelle Xiao-Hong Yan ,  Ti-Chiun Chang ,  Markus Lendl ,  Stefan Boehm ,  Tong Fang ,  Peter Durlak

发明人： Michelle Xiao-Hong Yan ,  Ti-Chiun Chang ,  Markus Lendl ,  Stefan Boehm ,  Tong Fang ,  Peter Durlak

IPC分类号： G06K9/00

CPC分类号： G06K9/4619 ,  G06K2209/05 ,  G06T7/0012

摘要： A method and system for image quality assessment is disclosed. The image quality assessment method is a no-reference method for objectively assessing the quality of medical images. This method is guided by the human vision model in order to accurately reflect human perception. A region of interest (ROI) of medical image is divided into non-overlapping blocks of equal size. Each of the blocks is categorized as a smooth block, a texture block, or an edge block. A perceptual sharpness measure, which is weighted by local contrast, is calculated for each of the edge blocks. A perceptual noise level measure, which is weighted by background luminance, is calculated for each of the smooth blocks. A sharpness quality index is determined based on the perceptual sharpness measures of all of the edge blocks, and a noise level quality index is determined based on the perceptual noise level measures of all of the smooth blocks. An overall image quality index can be determined by using task specific machine learning of samples of annotated images. The image quality assessment method can be used in applications, such as video/image compression and storage in healthcare and homeland security, and band-width limited wireless communication.

摘要翻译： 公开了一种用于图像质量评估的方法和系统。 图像质量评估方法是客观评估医学图像质量的非参考方法。 这种方法是以人类视觉模型为指导，以准确反映人类的感知。 医学图像的感兴趣区域（ROI）被划分成相等大小的不重叠块。 每个块被分类为平滑块，纹理块或边缘块。 针对每个边缘块计算出由局部对比度加权的感知锐度度量。 为每个平滑块计算感知噪声水平测量，其由背景亮度加权。 基于所有边缘块的感知锐度测量来确定锐度质量指标，并且基于所有平滑块的感知噪声水平测量来确定噪声水平质量指数。 可以通过使用注释图像的样本的任务特定机器学习来确定整体图像质量指数。 图像质量评估方法可用于医疗保健和国土安全中的视频/图像压缩和存储等应用，以及带宽有限的无线通信。

公开(公告)号：US20110064285A1

公开(公告)日：2011-03-17

申请号：US12846273

申请日：2010-07-29

申请人： Yunqiang Chen ,  Ti-chiun Chang ,  Michelle Xiaohong Yan ,  Tong Fang ,  Thomas Pohl ,  Stefan Böhm ,  Peter Durlak ,  Markus Roßmeier

发明人： Yunqiang Chen ,  Ti-chiun Chang ,  Michelle Xiaohong Yan ,  Tong Fang ,  Thomas Pohl ,  Stefan Böhm ,  Peter Durlak ,  Markus Roßmeier

IPC分类号： G06K9/00

CPC分类号： G06K9/6206 ,  G06K2209/057 ,  G06T5/001 ,  G06T5/20 ,  G06T5/50 ,  G06T2207/10016 ,  G06T2207/10121 ,  G06T2207/30101

摘要： A method for enhancing stent visibility in digital medical images includes providing a time series of 2-dimensional (2D) images of a stent in a vessel, estimating motion of the stent in a subset of images of the time series of images, estimating motion of clutter in the subset of images, where clutter comprises anatomical structures other than the stent, estimating a clutter layer in the subset of images from the estimated clutter motion, estimating a stent layer in the subset of images from the clutter layer and the estimated clutter motion, and minimizing a functional of the estimated stent motion, the estimated stent layer, the estimated clutter motion, and the estimated clutter layer to in calculate a refined stent layer image, where the refined stent layer image has enhanced visibility of the stent.

摘要翻译： 一种用于增强数字医学图像中的支架可视性的方法包括在血管中提供支架的二维（2D）图像的时间序列，估计支架在时间序列图像的图像的子集中的运动，估计运动 在图像子集中混乱，其中杂波包括除了支架之外的解剖结构，从估计的杂波运动估计图像子集中的杂波层，估计来自杂波层的图像子集中的支架层和估计的杂波运动 并且在计算精制的支架层图像时，将精确的支架层图像具有增强的支架的可视性，并且将估计的支架运动，估计的支架层，估计的杂波运动和估计的杂波层的功能最小化。

公开(公告)号：US08073191B2

公开(公告)日：2011-12-06

申请号：US12283357

申请日：2008-09-11

申请人： Ti-chiun Chang ,  Yunqiang Chen ,  Tong Fang ,  Sandra Martin ,  Stefan Böhm ,  Peter Durlak

发明人： Ti-chiun Chang ,  Yunqiang Chen ,  Tong Fang ,  Sandra Martin ,  Stefan Böhm ,  Peter Durlak

IPC分类号： G06K9/00

CPC分类号： G06K9/346 ,  G06K2209/05 ,  G06T5/005 ,  G06T5/20 ,  G06T2207/10116 ,  G06T2207/20012 ,  G06T2207/20076 ,  G06T2207/30004

摘要： A method and system for correcting butting artifacts in x-ray images is disclosed. In order to correct a butting artifact in an x-ray image, a butting artifact region in the x-ray image is normalized. Multiple intensity shift estimators are calculated for each pixel of each line of the butting artifact. Confidence intervals are calculated for each intensity shift estimator. A multiple hypothesis hidden Markov model (MH-HMM) is formulated based on the intensity shift operators and confidence measures subject to a smoothness constraint, and the MH-HMM is solved to determine intensity shift values for each pixel. A corrected image is generated by adjusting the intensity of each pixel of the butting artifact based on the intensity shift value for that pixel.

摘要翻译： 公开了一种用于校正X射线图像中的伪像的方法和系统。 为了校正X射线图像中的对接伪影，对x射线图像中的对接伪影区域进行归一化。 针对对接工件的每一行的每个像素计算多个强度偏移估计量。 为每个强度偏移估计器计算置信区间。 基于强度偏移算子和基于平滑度约束的置信度度度，制定了多重假设隐马尔可夫模型（MH-HMM），并求解了MH-HMM，以确定每个像素的强度偏移值。 通过基于该像素的强度偏移值调整对接伪影的每个像素的强度来生成校正图像。

公开(公告)号：US08433115B2

公开(公告)日：2013-04-30

申请号：US12846273

申请日：2010-07-29

申请人： Yunqiang Chen ,  Ti-chiun Chang ,  Michelle Xiaohong Yan ,  Tong Fang ,  Thomas Pohl ,  Stefan Böhm ,  Peter Durlak ,  Markus Roβmeier

发明人： Yunqiang Chen ,  Ti-chiun Chang ,  Michelle Xiaohong Yan ,  Tong Fang ,  Thomas Pohl ,  Stefan Böhm ,  Peter Durlak ,  Markus Roβmeier

IPC分类号： G06K9/00

CPC分类号： G06K9/6206 ,  G06K2209/057 ,  G06T5/001 ,  G06T5/20 ,  G06T5/50 ,  G06T2207/10016 ,  G06T2207/10121 ,  G06T2207/30101

摘要： A method for enhancing stent visibility in digital medical images includes providing a time series of 2-dimensional (2D) images of a stent in a vessel, estimating motion of the stent in a subset of images of the time series of images, estimating motion of clutter in the subset of images, where clutter comprises anatomical structures other than the stent, estimating a clutter layer in the subset of images from the estimated clutter motion, estimating a stent layer in the subset of images from the clutter layer and the estimated clutter motion, and minimizing a functional of the estimated stent motion, the estimated stent layer, the estimated clutter motion, and the estimated clutter layer to in calculate a refined stent layer image, where the refined stent layer image has enhanced visibility of the stent.

摘要翻译： 一种用于增强数字医学图像中的支架可视性的方法包括在血管中提供支架的二维（2D）图像的时间序列，估计支架在时间序列图像的图像的子集中的运动，估计运动 在图像子集中混乱，其中杂波包括除了支架之外的解剖结构，从估计的杂波运动估计图像子集中的杂波层，估计来自杂波层的图像子集中的支架层和估计的杂波运动 并且在计算精制的支架层图像时，将精确的支架层图像具有增强的支架的可视性，并且将估计的支架运动，估计的支架层，估计的杂波运动和估计的杂波层的功能最小化。

公开(公告)号：US20090080756A1

公开(公告)日：2009-03-26

申请号：US12283357

申请日：2008-09-11

申请人： Ti-chiun Chang ,  Yunqiang Chen ,  Tong Fang ,  Sandra Martin ,  Stefan Bohm ,  Peter Durlak

发明人： Ti-chiun Chang ,  Yunqiang Chen ,  Tong Fang ,  Sandra Martin ,  Stefan Bohm ,  Peter Durlak

IPC分类号： G06K9/00

CPC分类号： G06K9/346 ,  G06K2209/05 ,  G06T5/005 ,  G06T5/20 ,  G06T2207/10116 ,  G06T2207/20012 ,  G06T2207/20076 ,  G06T2207/30004

摘要： A method and system for correcting butting artifacts in x-ray images is disclosed. In order to correct a butting artifact in an x-ray image, a butting artifact region in the x-ray image is normalized. Multiple intensity shift estimators are calculated for each pixel of each line of the butting artifact. Confidence intervals are calculated for each intensity shift estimator. A multiple hypothesis hidden Markov model (MH-HMM) is formulated based on the intensity shift operators and confidence measures subject to a smoothness constraint, and the MH-HMM is solved to determine intensity shift values for each pixel. A corrected image is generated by adjusting the intensity of each pixel of the butting artifact based on the intensity shift value for that pixel.

摘要翻译： 公开了一种用于校正X射线图像中的伪像的方法和系统。 为了校正X射线图像中的对接伪影，对x射线图像中的对接伪影区域进行归一化。 针对对接工件的每一行的每个像素计算多个强度偏移估计量。 为每个强度偏移估计器计算置信区间。 基于强度偏移算子和基于平滑度约束的置信度度度，制定了多重假设隐马尔可夫模型（MH-HMM），并求解了MH-HMM，以确定每个像素的强度偏移值。 通过基于该像素的强度偏移值调整对接伪影的每个像素的强度来生成校正图像。

公开(公告)号：US08355557B2

公开(公告)日：2013-01-15

申请号：US12571487

申请日：2009-10-01

申请人： Yunqiang Chen ,  Ti-chiun Chang ,  Tong Fang ,  Sandra Knoth ,  Stefan Böhm ,  Peter Durlak

发明人： Yunqiang Chen ,  Ti-chiun Chang ,  Tong Fang ,  Sandra Knoth ,  Stefan Böhm ,  Peter Durlak

IPC分类号： G06K9/00 ,  A61B6/02 ,  A61B6/00

CPC分类号： G06T5/50 ,  G06T2207/20224 ,  G06T2207/30041 ,  G06T2207/30101

摘要： A method for temporally filtering medical images during a fluoroscopy guided intervention procedure includes providing a mask image, a fluoroscopy intervention image acquired at a current time during a medical intervention procedure, forming a subtraction image by subtracting the mask image from the intervention image, calculating a motion image of a moving structure in the subtraction image, forming a residual image by subtracting the motion image from the subtraction image, temporally filtering the residual image with a filtered image from a previous time, and adding the motion image to the temporally filtered residual image.

摘要翻译： 一种在荧光透视引导介入手术过程中对医学图像进行临时过滤的方法包括提供掩模图像，在医疗介入过程中当前时间获取的荧光透视干预图像，通过从干预图像中减去掩模图像形成减影图像， 在减法图像中的运动结构的运动图像，通过从减法图像中减去运动图像形成残差图像，并用先前时间用滤波图像对剩余图像进行时间滤波，并将运动图像与时间滤波残差图像相加 。

公开(公告)号：US20100092061A1

公开(公告)日：2010-04-15

申请号：US12571487

申请日：2009-10-01

申请人： Yunqiang Chen ,  Ti-chiun Chang ,  Tong Fang ,  Sandra Knoth ,  Stefan Böhm ,  Peter Durlak

发明人： Yunqiang Chen ,  Ti-chiun Chang ,  Tong Fang ,  Sandra Knoth ,  Stefan Böhm ,  Peter Durlak

IPC分类号： G06K9/00

CPC分类号： G06T5/50 ,  G06T2207/20224 ,  G06T2207/30041 ,  G06T2207/30101

摘要： A method for temporally filtering medical images during a fluoroscopy guided intervention procedure includes providing a mask image, a fluoroscopy intervention image acquired at a current time during a medical intervention procedure, forming a subtraction image by subtracting the mask image from the intervention image, calculating a motion image of a moving structure in the subtraction image, forming a residual image by subtracting the motion image from the subtraction image, temporally filtering the residual image with a filtered image from a previous time, and adding the motion image to the temporally filtered residual image.

摘要翻译： 一种在荧光透视引导介入手术过程中对医学图像进行临时过滤的方法包括提供掩模图像，在医疗介入过程中当前时间获取的荧光透视干预图像，通过从干预图像中减去掩模图像形成减影图像， 在减法图像中的运动结构的运动图像，通过从减法图像中减去运动图像形成残差图像，并用先前时间用滤波图像对剩余图像进行时间滤波，并将运动图像与时间滤波残差图像相加 。

公开(公告)号：US08244020B2

公开(公告)日：2012-08-14

申请号：US12286992

申请日：2008-10-03

申请人： Yunqiang Chen ,  Tong Fang ,  Sandra Martin ,  Stefan Boehm ,  Peter Durlak

发明人： Yunqiang Chen ,  Tong Fang ,  Sandra Martin ,  Stefan Boehm ,  Peter Durlak

IPC分类号： G06K9/40 ,  G06K9/60 ,  G06T5/50 ,  G01N23/083

CPC分类号： A61B6/504 ,  A61B6/481 ,  A61B6/482 ,  G06K2009/00932

摘要： A method and system for intelligent digital subtraction is disclosed. The method and system for intelligent digital subtraction can be used in a roadmap application for a coronary intervention. A mask image is obtained with vessels highlighted by contrast media. A guide wire is inserted into the vessels, and a guide wire image is obtained. A direct subtraction image is generated from the guide wire image and the mask image. A reduced noise subtraction image is generated based on mutual image information between the subtraction image and the guide wire image and mutual image information between the subtraction image and the mask image.

摘要翻译： 公开了一种智能数字减法的方法和系统。 用于智能数字减法的方法和系统可用于冠状动脉干预的路线图应用。 用造影剂强调的血管获得掩模图像。 将引导线插入容器中，并获得导丝图像。 从引导线图像和掩模图像生成直接减法图像。 基于减法图像和引导线图像之间的相互图像信息以及减法图像和掩模图像之间的相互图像信息，生成降噪噪声减影图像。

公开(公告)号：US20090103682A1

公开(公告)日：2009-04-23

申请号：US12286992

申请日：2008-10-03

申请人： Yungiang Chen ,  Tong Fang ,  Sandra Martin ,  Stefan Boehm ,  Peter Durlak

发明人： Yungiang Chen ,  Tong Fang ,  Sandra Martin ,  Stefan Boehm ,  Peter Durlak

IPC分类号： H05G1/64 ,  G06K9/00

CPC分类号： A61B6/504 ,  A61B6/481 ,  A61B6/482 ,  G06K2009/00932

摘要： A method and system for intelligent digital subtraction is disclosed. The method and system for intelligent digital subtraction can be used in a roadmap application for a coronary intervention. A mask image is obtained with vessels highlighted by contrast media. A guide wire is inserted into the vessels, and a guide wire image is obtained. A direct subtraction image is generated from the guide wire image and the mask image. A reduced noise subtraction image is generated based on mutual image information between the subtraction image and the guide wire image and mutual image information between the subtraction image and the mask image.

摘要翻译： 公开了一种智能数字减法的方法和系统。 用于智能数字减法的方法和系统可用于冠状动脉干预的路线图应用。 用造影剂强调的血管获得掩模图像。 将引导线插入容器中，并获得导丝图像。 从引导线图像和掩模图像生成直接减法图像。 基于减法图像和引导线图像之间的相互图像信息以及减法图像和掩模图像之间的相互图像信息，生成降噪噪声减影图像。