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1. 发明申请

WO2009035564A1 AUTOMATIC LESION DETECTION AND CHARACTERIZATION USING A GENERATIVE MODEL OF CONTRAST ENHANCEMENT DYNAMICS IN DCE BREAST MRI 审中-公开
标题翻译：使用DCE BREAST MRI中对比增强动力学的一般模型的自动检测和特征
公开(公告)号：WO2009035564A1
公开(公告)日：2009-03-19
申请号：PCT/US2008/010492
申请日：2008-09-08
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
发明人： HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
IPC分类号： G01R33/28 , G01R33/56
CPC分类号： G01R33/5601 , G01R33/5608 , G06K9/38 , G06K2209/05 , G06T7/0012 , G06T2207/10088 , G06T2207/10096 , G06T2207/30004
摘要： A method for automatic detection of lesions within MR images includes administering a magnetic contrast agent into a subject (S41). A sequence of MR images are acquired at predetermined intervals of time (S42). One or more regions of suspicion are automatically identified within the MR images (S43). A bidirectional exchange of the magnetic contrast agent between each compartment and its neighboring compartment is monitored for each compartment within each region of suspicion (S44). Each region of suspicion is characterized based on the bidirectional exchange between each of its compartments and their neighboring compartments (S46).
摘要翻译：用于自动检测MR图像内的损伤的方法包括向对象施用磁性造影剂（S41）。以预定的时间间隔获取MR图像序列（S42）。在MR图像内自动识别一个或多个怀疑区域（S43）。监测每个隔间与其相邻隔室之间的磁性造影剂的双向交换，以便在每个怀疑区域内的每个隔间（S44）。基于每个隔间与其相邻的隔室之间的双向交换来表征每个怀疑区域（S46）。

2. 发明申请

WO2009035557A1 DETECTION OF MOTION ARTIFACTS IN DYNAMIC CONTRAST-ENHANCED BREAST MRI 审中-公开
标题翻译：动态对比增强乳腺MRI检测运动文献
公开(公告)号：WO2009035557A1
公开(公告)日：2009-03-19
申请号：PCT/US2008/010472
申请日：2008-09-08
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
发明人： HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
IPC分类号： G01R33/28 , G01R33/565
CPC分类号： G01R33/5601 , G01R33/56509
摘要： A method for identifying motion artifacts in a dynamic contrast enhanced MRI includes receiving a dynamic contrast enhanced MRI including a patient's breast on which motion correction has been performed. One or more regions of suspicion are automatically identified within the breast based in the dynamic contrast enhanced MRI. The regions of suspicion are examined (S41). A measure of negative enhancement is calculated within a local neighborhood about each identified region of suspicion (S42). Each identified region of suspicion for which the calculated measure of negative enhancement is greater than a predetermined threshold is removed (S49).
摘要翻译：用于识别动态对比度增强MRI中的运动伪影的方法包括：接收包括已进行运动校正的患者乳房的动态对比度增强MRI。在动态造影增强MRI中，一个或多个怀疑区域在乳房内自动识别。审查怀疑地区（S41）。在每个确定的怀疑区域内，在当地社区内计算消极增强的度量（S42）。消除了所计算的负增强度量大于预定阈值的怀疑区域（S49）。

3. 发明申请

WO2009035573A1 AUTOMATIC CALIBRATION OF COMPUTER AIDED DIAGNOSIS BASED ON RETROSPECTIVE EXAMINATION 审中-公开
标题翻译：基于回顾性检查的计算机辅助诊断的自动校准
公开(公告)号：WO2009035573A1
公开(公告)日：2009-03-19
申请号：PCT/US2008/010505
申请日：2008-09-08
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , SHINAGAWA, Yoshihisa , HERMOSILLO VALADEZ, Gerardo
发明人： SHINAGAWA, Yoshihisa , HERMOSILLO VALADEZ, Gerardo
IPC分类号： G06T7/00
CPC分类号： G06T7/0012
摘要： A method for automatic detection of lesions within a medical image include acquiring medical image data (S31). Regions of suspicion are automatically identified within the medical image data (S32). It is automatically determined whether each identified region of suspicion is of a benign state, is of a suspicious state that requires a biopsy, or is of an indeterminate state that requires subsequent imaging after a particular length of time (S33). When an identified region of suspicion is determined to be of an indeterminate state, the determination is automatically reconsidered in light of a calibration factor that biases the automatic determination towards either a benign state or a suspicious state (S36). The calibration factor may be based on data collected from follow-up examinations that reveal whether a lesion previously characterized as indeterminate was actually a benign or malignant lesion (S38) or on additional diagnostic information including prior image data or non-image data.
摘要翻译：医疗图像内的病变的自动检测方法包括取得医用图像数据（S31）。在医学图像数据内自动识别怀疑区域（S32）。自动确定每个识别的怀疑区域是否是良性状态，是否需要活组织检查的可疑状态，或者是在特定时间段之后需要后续成像的不确定状态（S33）。当识别到的怀疑区域被确定为不确定状态时，根据将自动判定偏向良性状态或可疑状态的校准因子自动重新确定（S36）。校正因子可以基于从随访检查收集的数据，其揭示先前特征为不确定性的病变实际上是良性或恶性病变（S38）或包括先前图像数据或非图像数据的附加诊断信息。

4. 发明申请

WO2009035672A1 ROBUST SEGMENTATION OF BREAST AND MUSCLE IN MRI 审中-公开
标题翻译：乳腺和肌肉在MRI中的稳定分期
公开(公告)号：WO2009035672A1
公开(公告)日：2009-03-19
申请号：PCT/US2008/010674
申请日：2008-09-12
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , SHINAGAWA, Yoshihisa , HERMOSILLO VALADEZ, Gerardo
发明人： SHINAGAWA, Yoshihisa , HERMOSILLO VALADEZ, Gerardo
IPC分类号： G06T5/00 , G06T5/10 , G06T11/00
CPC分类号： G06T11/003 , G06T7/11 , G06T7/168 , G06T2207/10088 , G06T2207/30068 , G06T2207/30096
摘要： A method for segmenting an anatomical structure within medical image data includes acquiring medical image data (S31). The medical image data is transformed from an original image space into a projective dual image space (S32). A boundary of an anatomical structure is identified within the transformed medical image data based on a set of preexisting training data (S33). An inverse transform is performed on the transformed medical image data and the identified boundary to convert the transformed medical image data and the identified boundary into the original image space (S34). The inverse transformed identified boundary of the anatomical structure is used to segment the anatomical structure within the acquired medical image data
摘要翻译：用于分割医学图像数据内的解剖结构的方法包括获取医学图像数据（S31）。医学图像数据从原始图像空间变换为投影双重图像空间（S32）。基于一组先前存在的训练数据，在经转换的医学图像数据内识别解剖结构的边界（S33）。对变换的医学图像数据和所识别的边界执行逆变换，以将转换的医学图像数据和所识别的边界转换成原始图像空间（S34）。解剖结构的逆变换识别边界用于分割所获取的医学图像数据内的解剖结构

5. 发明申请

WO2009035559A1 CORRECTION OF INTENSITY INHOMOGENEITY IN BREAST MRI 审中-公开
标题翻译：乳腺MRI中强度不均匀性的校正
公开(公告)号：WO2009035559A1
公开(公告)日：2009-03-19
申请号：PCT/US2008/010474
申请日：2008-09-08
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
发明人： HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
IPC分类号： G01R33/565
CPC分类号： G01R33/56563 , G01R33/281 , G01R33/5608
摘要： A method for correcting for magnetic field inhomogeneity in a breast MRI, includes acquiring a magnetic resonance (MR) image including a patient's breast (S31). A surface image of the breast is automatically isolated within the acquired MR image based on a high contrast between the breast and surrounding air (S32). A multiplicative field that transforms the isolated surface image into a uniform intensity is generated (S33). The generated multiplicative field is applied to the entire acquired MR image to produce a corrected image (S34).
摘要翻译：一种用于校正乳房MRI中的磁场不均匀性的方法，包括获取包括患者乳房的磁共振（MR）图像（S31）。基于乳房和周围空气之间的高对比度，乳房的表面图像在所获取的MR图像内被自动隔离（S32）。产生将孤立表面图像变换为均匀强度的乘法场（S33）。生成的乘法场被施加到整个获取的MR图像以产生校正图像（S34）。

6. 发明申请

WO2009035555A1 EFFICIENT FEATURES FOR SHAPE ANALYSIS OF LESIONS IN BREAST MR 审中-公开
标题翻译：乳腺切片形态分析的有效特征MR
公开(公告)号：WO2009035555A1
公开(公告)日：2009-03-19
申请号：PCT/US2008/010467
申请日：2008-09-08
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , SHINAGAWA, Yoshihisa , HERMOSILLO VALADEZ, Gerardo
发明人： SHINAGAWA, Yoshihisa , HERMOSILLO VALADEZ, Gerardo
IPC分类号： G06K9/64 , G06T7/00
CPC分类号： G06T7/0012 , G06K9/469 , G06T2207/10088 , G06T2207/20072 , G06T2207/30068
摘要： A method for analyzing a shape of a region of interest in a medical image of a body part, including: finding a region of interest in the medical image (410); calculating a Reeb graph of the region of interest (420); and determining whether the region of interest is a malignant lesion candidate based on a shape characteristic of the Reeb graph (430).
摘要翻译：一种用于分析身体部位的医学图像中的感兴趣区域的形状的方法，包括：找到医疗图像中的感兴趣区域（410）; 计算感兴趣区域的Reeb图（420）; 以及基于所述Reeb图形的形状特征来确定所述感兴趣区域是否为恶性病变候选。

7. 发明申请

WO2009035609A1 MULTI-SCALE ANALYSIS OF SIGNAL ENHANCEMENT IN BREAST MRI 审中-公开
标题翻译： BREAST MRI中信号增强的多尺度分析
公开(公告)号：WO2009035609A1
公开(公告)日：2009-03-19
申请号：PCT/US2008/010581
申请日：2008-09-10
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , SHINAGAWA, Yoshihisa , HERMOSILLO VALADEZ, Gerardo
发明人： SHINAGAWA, Yoshihisa , HERMOSILLO VALADEZ, Gerardo
IPC分类号： G01R33/28
CPC分类号： G01R33/5601 , G01R33/5608 , G06K9/4609 , G06K2209/05 , G06T5/50 , G06T7/0012 , G06T7/11 , G06T7/174 , G06T2207/10088 , G06T2207/20224 , G06T2207/30068 , G06T2207/30096
摘要： A method for computer assisted lesion detection in magnetic resonance (MR) images includes acquiring dynamic contrast enhanced (DCE) MR images (S31). The images are processed to produce a subtraction image illustrating change in voxel enhancement between the images (S32). A Gaussian low-pass filter is applied to the subtraction image (S33). An elimination mask is created from the filtered subtraction image by removing voxels with enhancement values below a threshold value (S34). The elimination mask is used to remove noise from the subtraction image (S35). One or more regions of suspicion are automatically detected from the noise-removed subtraction image. To produce the subtraction image, DCE-MR images are divided into first and second sub-sets. Positive-signed enhancement values of voxels of the MR images from the first sub-set are added to a combined subtraction image along with absolute values of all enhancement values of voxels of the MR images from the second sub-set.
摘要翻译：用于磁共振（MR）图像中计算机辅助病变检测的方法包括采集动态对比度增强（DCE）MR图像（S31）。对图像进行处理以产生图像中的体素增强的变化的减法图像（S32）。将高斯低通滤波器应用于减法图像（S33）。通过去除具有低于阈值的增强值的体素从滤波的减法图像中创建消除掩模（S34）。消除掩模用于从减法图像中去除噪声（S35）。从噪声消除的减影图像中自动检测一个或多个怀疑区域。为了产生减法图像，DCE-MR图像被分成第一和第二子集。来自第一子集的MR图像的体素的正号增强值与来自第二子集的MR图像的体素的所有增强值的绝对值相加到组合减影图像。

8. 发明申请

WO2009035572A1 AUTOMATIC LESION CORRELATION IN MULTIPLE MR MODALITIES 审中-公开
标题翻译：多种MR模式中的自动关联相关性
公开(公告)号：WO2009035572A1
公开(公告)日：2009-03-19
申请号：PCT/US2008/010504
申请日：2008-09-08
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
发明人： HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
IPC分类号： G06T7/00
CPC分类号： G06T7/38
摘要： A method for automatic correlation between multiple magnetic resonance (MR) modalities includes acquiring first MR image data form a first modality (S45). Second MR image data is acquired from a second modality (S46). One or more anatomical landmarks are detected within both the first and second MR image data and the first and second MR image data are automatically correlated based on the detected anatomical landmarks and interpolation using a learning deformation function (S47). The automatic correlation is refined using a local search (S48).
摘要翻译：一种用于多个磁共振（MR）模态之间的自相关的方法包括从第一模态获取第一MR图像数据（S45）。从第二模式获取第二MR图像数据（S46）。在第一和第二MR图像数据中都检测到一个或多个解剖标志，并且基于检测到的解剖标志和使用学习变形函数进行插值，第一和第二MR图像数据被自动相关（S47）。使用本地搜索来改进自动相关（S48）。

9. 发明申请

WO2009035556A2 ALIGNMENT OF FAT-SAT AND NON-FAT-SAT T1 WEIGHTED IMAGES IN MRI APPLICATIONS 审中-公开
标题翻译： MRI应用中FAT-SAT和非FAT-T1 T1加权图像的对齐
公开(公告)号：WO2009035556A2
公开(公告)日：2009-03-19
申请号：PCT/US2008/010471
申请日：2008-09-08
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
发明人： HERMOSILLO VALADEZ, Gerardo , SHINAGAWA, Yoshihisa
IPC分类号： G01R33/56
CPC分类号： G01R33/56 , G01R33/4828 , G01R33/5607 , G01R33/5608 , G06T7/35 , G06T2207/10088 , G06T2207/30004
摘要： A method for aligning medical images, including: generating a learned joint distribution of intensities of corresponding voxels of images acquired by a first modality and a second modality, wherein the first and second modalities are different from each other; acquiring a first image of a patient using the first modality (310); acquiring a second image of the patient using the second modality (320); and aligning the first and second images based on the learned joint distribution (330).
摘要翻译：一种用于对齐医学图像的方法，包括：生成由第一模态和第二模态获取的图像的对应体素的强度的学习联合分布，其中第一模态和第二模态彼此不同 ; 使用第一模态获取患者的第一图像（310）; 使用第二模态获取患者的第二图像（320）; 并基于学习的联合分布（330）对齐第一和第二图像。

10. 发明申请

WO2009017746A2 EXPANDED PHARMACOKINETIC MODEL FOR POPULATION STUDIES IN BREAST MAGNETIC RESONANCE IMAGING (MRI) 审中-公开
标题翻译：扩展的药物动力学模型用于人类乳腺磁共振成像研究（MRI）
公开(公告)号：WO2009017746A2
公开(公告)日：2009-02-05
申请号：PCT/US2008/009189
申请日：2008-07-30
申请人： SIEMENS MEDICAL SOLUTIONS USA, INC. , SHINAGAWA, Yoshihisa , MOHAN, Vandana , HERMOSILLO VALADEZ, Gerardo
发明人： SHINAGAWA, Yoshihisa , MOHAN, Vandana , HERMOSILLO VALADEZ, Gerardo
IPC分类号： G06T7/00
CPC分类号： G06T7/0012 , G01R33/5601 , G01R33/56366 , G06T2207/30068
摘要： A method for pharmacokinetic analysis, including: receiving time-series medical image data of a patient introduced with a contrast agent (505); identifying a reference region in the medical image data (510); identifying a plurality of points of interest in the medical image data (515); measuring an intensity of voxels in the reference region (520); and for each point of interest, measure an intensity of voxels therein (525), use the measured reference region and point of interest intensities to obtain an expression relating the point of interest's voxel concentration to that of the reference region (530), wherein the expression is a five-parameter nonlinear model with no reference to an arterial input function; and obtain values for each of the five-parameters by solving the expression (535) and use the obtained values to determine whether the point of interest is malignant (540). (FIG. 5)
摘要翻译：一种用于药代动力学分析的方法，包括：接收引入了造影剂的患者的时间序列医学图像数据（505）; 识别医学图像数据中的参考区域（510）; 识别医学图像数据中的多个兴趣点（515）; 测量参考区域（520）中体素的强度; 并且对于每个兴趣点，测量其中的体素的强度（525），使用测量的参考区域和兴趣点强度来获得将兴趣点的体素浓度与参考区域的体素浓度关联起来的表达式（530），其中，表达式是不参考动脉输入函数的五参数非线性模型; 并通过求解表达式（535）获得五个参数中的每一个的值并使用所获得的值来确定感兴趣点是否是恶性的（540）。（图5）

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