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71. 发明申请

US20100142789A1 METHOD FOR CORRECTING MOTION ARTIFACTS IN MAGNETIC RESONANCE IMAGES 有权
标题翻译：用于校正磁共振图像中的运动文学的方法
公开(公告)号：US20100142789A1
公开(公告)日：2010-06-10
申请号：US12632240
申请日：2009-12-07
申请人： Ti-chiun Chang , Tong Fang , Michelle Xiaohong Yan
发明人： Ti-chiun Chang , Tong Fang , Michelle Xiaohong Yan
IPC分类号： G06K9/00 , A61B5/055
CPC分类号： A61B6/03 , A61B5/055 , A61B5/7207 , G01R33/5608 , G01R33/56509
摘要： For resonance image data of an imaged subject, a method that first detects and estimates the dominant motions of k-space data (i.e., the motion vectors) and then constructs a graphical model for each estimated motion vector. The segments of the k-space that are determined to be corrupted by motion are restored by minimizing the energy associated with the corresponding graphical model. Consequently, the MR image of the imaged subject becomes free of motion artifacts.
摘要翻译：对于成像对象的共振图像数据，首先检测并估计k空间数据的主要运动（即，运动矢量），然后为每个估计运动矢量构建图形模型的方法。通过最小化与相应的图形模型相关联的能量来恢复被确定为被运动破坏的k空间的段。因此，成像对象的MR图像变得没有运动伪像。

72. 发明申请

US20090148016A1 Method and system for second bend plane detection of ear canal surfaces 失效
标题翻译：耳道表面第二次弯曲面检测方法与系统
公开(公告)号：US20090148016A1
公开(公告)日：2009-06-11
申请号：US12313600
申请日：2008-11-21
申请人： Gregory G. Slabaugh , Tong Fang , Rupen Melkisetoglu , Simon Floery
发明人： Gregory G. Slabaugh , Tong Fang , Rupen Melkisetoglu , Simon Floery
IPC分类号： G06K9/00
CPC分类号： G06T19/00 , G06F17/50 , G06T7/13 , G06T2207/20164 , G06T2219/008 , H04R25/652 , H04R25/658 , H04R2225/77
摘要： A method and system for detecting the second bend plane of an ear canal surface is disclosed. A region of interest of the ear canal is defined between the first bend plane and the ear canal tip. A set of curves is defined in the region of interest and a set of high curvature points is detected from the set of curves. The second bend plane is detected using the set of high curvature points.
摘要翻译：公开了一种用于检测耳道表面的第二弯曲面的方法和系统。在第一弯曲平面和耳道尖之间限定耳道感兴趣的区域。在感兴趣区域中定义一组曲线，并从该组曲线中检测出一组高曲率点。使用一组高曲率点检测第二弯曲平面。

73. 发明申请

US20090116731A1 Method and system for detection of concha and intertragal notch point in 3D undetailed ear impressions 审中-公开
标题翻译：用于检测三维未确定耳朵印迹中的外耳和交错切口点的方法和系统
公开(公告)号：US20090116731A1
公开(公告)日：2009-05-07
申请号：US12288216
申请日：2008-10-17
申请人： Rupen Melkisetoglu , Alexander Zouhar , Tong Fang
发明人： Rupen Melkisetoglu , Alexander Zouhar , Tong Fang
IPC分类号： G06K9/00
CPC分类号： G06T7/60 , A61B5/107 , G06K9/00201 , G06K9/468 , G06T2207/10028 , G06T2207/30004 , H04R25/652 , H04R25/658 , H04R2225/77
摘要： A method and system for detecting the concha and intertragal notch in an undetailed 3D ear impression is disclosed. The concha is detected by searching vertical scan lines in a region surrounding the aperture using a two-pass method. The intertragal notch is detected based on a bottom contour of the 3D undetailed ear impression and a local coordinate system defined for the 3D undetailed ear impression.
摘要翻译：公开了一种用于检测未详细3D耳朵印象中的外耳和内耳切口的方法和系统。通过使用双程法搜索围绕孔径的区域中的垂直扫描线来检测外耳。基于3D未详细耳朵印象的底部轮廓和为3D未详细耳朵印象定义的局部坐标系来检测相互间差距。

74. 发明申请

US20090116713A1 Method and system for human vision model guided medical image quality assessment 有权
标题翻译：人类视觉模型的方法与系统指导医学图像质量评估
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。

75. 发明申请

US20080260221A1 System and Method for Lesion Segmentation in Whole Body Magnetic Resonance Images 有权
标题翻译：全身磁共振图像中病变分割的系统和方法
公开(公告)号：US20080260221A1
公开(公告)日：2008-10-23
申请号：US12045327
申请日：2008-03-10
申请人： Gozde Unal , Gregory G. Slabaugh , Tong Fang , Shawn Linkton , Valer Canda , Stefan Thesen , Shuping Qing
发明人： Gozde Unal , Gregory G. Slabaugh , Tong Fang , Shawn Linkton , Valer Canda , Stefan Thesen , Shuping Qing
IPC分类号： G06K9/00
CPC分类号： G06K9/6207 , G06F19/00 , G06K9/342 , G06K2009/366 , G06K2209/053 , G06T7/12 , G06T7/149 , G06T7/194 , G06T2200/04 , G06T2207/10088 , G06T2207/20104 , G06T2207/30096
摘要： A method for lesion segmentation in 3-dimensional (3D) digital images, includes selecting a 2D region of interest (ROI) from a 3D image, the ROI containing a suspected lesion, extending borders of the ROI to 3D forming a volume of interest (VOI), where voxels on the borders of the VOI are initialized as background voxels and voxels in an interior of the VOI are initialized as foreground voxels, propagating a foreground and background voxel competition where for each voxel in the VOI, having each neighbor voxel in a neighborhood of the voxel attack the voxel, and, if the attack is successful, updating a label and strength of the voxel with that of the successful attacking voxel, and evolving a surface between the foreground and background voxels in 3D until an energy functional associated with the surface converges in value, where the surface segments the suspected lesion from the image.
摘要翻译：一种用于三维（3D）数字图像中的病变分割的方法，包括从3D图像中选择感兴趣的2D区域（ROI），ROI包含疑似病变，将ROI的边界延伸到形成感兴趣体积的3D（ VOI），其中VOI边界上的体元被初始化为背景体元素，并且VOI内部的体素被初始化为前景体素，传播前景和背景体素竞争，其中对于VOI中的每个体素，具有每个相邻体素体素的邻域攻击体素，并且如果攻击成功，更新体素的标签和强度与成功的攻击体素的标记和强度，并且以3D形式在前景和背景体素之间演变出一个表面，直到能量功能相关其表面收敛于值，其中表面将图像中的可疑病变分割。

76. 发明申请

US20080112649A1 Method and System for Dual Energy Image Registration 有权
标题翻译：双能量图像配准方法与系统
公开(公告)号：US20080112649A1
公开(公告)日：2008-05-15
申请号：US11934273
申请日：2007-11-02
申请人： Yunqiang Chen , Tong Fang
发明人： Yunqiang Chen , Tong Fang
IPC分类号： G06K9/60
CPC分类号： G06K9/32 , G06K9/6857
摘要： A method and system for dual energy image registration is disclosed. In order to segment first and second images of a dual energy image pair, the first and second images are preprocessed to detect edges in the images. Gaussian pyramids, having multiple pyramid images corresponding to multiple pyramid levels, are generated for the first and second images. An initial optical flow value is initialized for a first pyramid level, and the optical flow value is sequentially updated for each pyramid level based on the corresponding pyramid images using an optimization function having a similarity measure and a regularizer. This results in a final optical flow value between the first and second images, and the first and second images are registered based on the final optical flow value.
摘要翻译：公开了一种用于双能量图像配准的方法和系统。为了分割双能量图像对的第一和第二图像，第一和第二图像被预处理以检测图像中的边缘。对于第一和第二图像，生成具有对应于多个金字塔级别的多个金字塔图像的高斯金字塔。对于第一金字塔级别初始化初始光流值，并且使用具有相似性度量和正则化器的优化函数，基于相应的金字塔图像，针对每个金字塔级别顺序更新光流值。这导致第一和第二图像之间的最终光流值，并且基于最终光流值登记第一和第二图像。

77. 发明申请

US20080075345A1 Method and System For Lymph Node Segmentation In Computed Tomography Images 审中-公开
标题翻译：计算机断层扫描图像中淋巴结分割的方法和系统
公开(公告)号：US20080075345A1
公开(公告)日：2008-03-27
申请号：US11857801
申请日：2007-09-19
申请人： Gozde Unal , Atilla Kiraly , Gregory Slabaugh , Carol Novak , Tong Fang
发明人： Gozde Unal , Atilla Kiraly , Gregory Slabaugh , Carol Novak , Tong Fang
IPC分类号： G06K9/62
CPC分类号： G06T7/149 , G06T7/12 , G06T2207/10081 , G06T2207/20116 , G06T2207/30096
摘要： A method and system for lymph node segmentation in computed tomography (CT) images is disclosed. A location of a lymph node in a CT image slice is received. Intensity constraints are determined based on a histogram analysis of the CT image slice, and a spatial analysis of the intensity constrained CT image slice is performed using edge detection. An initial contour is estimated based on the lymph node location and the spatial analysis. The lymph node is then segmented by propagating the initial contour using an evolving elliptical model to define the lymph node boundaries.
摘要翻译：公开了一种计算机断层扫描（CT）图像中淋巴结分割的方法和系统。接收CT图像切片中淋巴结的位置。强度约束基于CT图像切片的直方图分析确定，并且使用边缘检测进行强度约束CT图像切片的空间分析。基于淋巴结位置和空间分析估计初始轮廓。然后通过使用演进的椭圆模型传播初始轮廓来分割淋巴结以限定淋巴结边界。

78. 发明授权

US07286679B2 Automatic binaural shell modeling for hearing aids 有权
标题翻译：用于助听器的自动双耳壳建模
公开(公告)号：US07286679B2
公开(公告)日：2007-10-23
申请号：US10739732
申请日：2003-12-18
申请人： Tong Fang , Jason Jenn-Kwei Tyan , Ming Fang
发明人： Tong Fang , Jason Jenn-Kwei Tyan , Ming Fang
IPC分类号： H04R25/00
CPC分类号： H04R25/658 , B33Y80/00 , H04R25/552 , H04R25/652 , H04R2225/77 , Y10T29/49572
摘要： A system and method for modeling binaural shells for hearing aids, wherein the system is configured to load data associated with a first and a second ear shell. The system is further configured to register the data associated with the first and the second ear shells and process the first ear shell and the second ear shells, wherein the processing on the first ear shell is automatically performed on the second ear shell.
摘要翻译：一种用于对用于助听器的双耳壳进行建模的系统和方法，其中所述系统被配置为加载与第一耳壳和第二耳壳相关联的数据。该系统还被配置为登记与第一耳壳和第二耳壳相关联的数据并处理第一耳壳和第二耳壳，其中在第二耳壳上自动执行对第一耳壳的处理。

79. 发明申请

US20070206880A1 Coupled Bayesian Framework For Dual Energy Image Registration 审中-公开
标题翻译：耦合贝叶斯框架双能量图像注册
公开(公告)号：US20070206880A1
公开(公告)日：2007-09-06
申请号：US11563815
申请日：2006-11-28
申请人： Yunqiang Chen , Hao Wu , Tong Fang
发明人： Yunqiang Chen , Hao Wu , Tong Fang
IPC分类号： G06K9/32 , G06K9/00
CPC分类号： G06K9/00 , G06K9/6206 , G06K2209/05 , G06T7/344
摘要： A computer implemented method for joint image registration and reconstruction of a plurality of images includes providing the plurality of images, modeling the plurality of images, including reconstructing bone and soft-tissue in respective images of the plurality of images, performing a hierarchical free-form registration of models of the plurality of images to determine a jointly registered and reconstructed image with successive accuracy adjustment according to a registration error, and outputting the registered and reconstructed image.
摘要翻译：用于联合图像配准和重建多个图像的计算机实现方法包括提供多个图像，对多个图像进行建模，包括在多个图像的各个图像中重建骨骼和软组织，执行分层自由形式登记多个图像的模型，以根据注册错误来确定具有连续精度调整的联合登记和重建图像，并输出注册和重建的图像。

80. 发明申请

US20070167710A1 Method and Apparatus for Inner Wall Extraction and Stent Strut Detection Using Intravascular Optical Coherence Tomography Imaging 有权
标题翻译：使用血管内光学相干断层扫描成像的内壁提取和支架支架检测的方法和装置
公开(公告)号：US20070167710A1
公开(公告)日：2007-07-19
申请号：US11555806
申请日：2006-11-02
申请人： Gozde Unal , Yan Yang , Gregory Slabaugh , Tong Fang
发明人： Gozde Unal , Yan Yang , Gregory Slabaugh , Tong Fang
IPC分类号： A61B5/05
CPC分类号： A61B5/6852 , A61B5/0066 , A61B5/0086
摘要： A method and apparatus for automatically detecting stent struts in an image is disclosed whereby the inner boundary, or lumen, of an artery wall is first detected automatically and intensity profiles along rays in the image are determined. In one embodiment, detection of the lumen boundary may be accomplished, for example, by evolving a geometric shape, such as an ellipse, using a region-based algorithm technique, a geodesic boundary-based algorithm technique or a combination of the two techniques. Once the lumen boundary has been determined, in another embodiment, the stent struts are detected using a ray shooting algorithm whereby a ray is projected outward in the OCT image starting from the position in the image of the OCT sensor. The intensities of the pixels along the ray are used to detect the presence of a stent strut in the image.
摘要翻译：公开了一种用于自动检测图像中的支架支柱的方法和装置，其中首先自动检测动脉壁的内边界或内腔，并且确定与图像中的光线的强度分布。在一个实施例中，可以例如通过使用基于区域的算法技术，基于测地边界的算法技术或两种技术的组合来演示诸如椭圆的几何形状来实现流明边界的检测。一旦已经确定了管腔边界，在另一个实施例中，使用射线射击算法来检测支架支柱，由此射线从OCT传感器的图像中的位置开始向OCT中投射。使用沿着光线的像素的强度来检测图像中支架支柱的存在。

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