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1.发明授权Method and system for hemodynamic assessment of aortic coarctation from medical image data 有权医学图像数据主动脉缩窄血流动力学评估方法与系统公开(公告)号：US09135699B2
公开(公告)日：2015-09-15
申请号：US13826307
申请日：2013-03-14
申请人： Kristof Ralovich , Lucian Mihai Itu , Viorel Mihalef , Puneet Sharma , Razvan Ioan Ionasec , Dime Vitanovski , Waldemar Krawtschuk , Dorin Comaniciu
发明人： Kristof Ralovich , Lucian Mihai Itu , Viorel Mihalef , Puneet Sharma , Razvan Ioan Ionasec , Dime Vitanovski , Waldemar Krawtschuk , Dorin Comaniciu
CPC分类号： G06T7/0012 , G06T2207/10076 , G06T2207/10096 , G06T2207/30104
摘要： A method and system for non-invasive hemodynamic assessment of aortic coarctation from medical image data, such as magnetic resonance imaging (MRI) data is disclosed. Patient-specific lumen anatomy of the aorta and supra-aortic arteries is estimated from medical image data of a patient, such as contrast enhanced MRI. Patient-specific aortic blood flow rates are estimated from the medical image data of the patient, such as velocity encoded phase-contrasted MRI cine images. Patient-specific inlet and outlet boundary conditions for a computational model of aortic blood flow are calculated based on the patient-specific lumen anatomy, the patient-specific aortic blood flow rates, and non-invasive clinical measurements of the patient. Aortic blood flow and pressure are computed over the patient-specific lumen anatomy using the computational model of aortic blood flow and the patient-specific inlet and outlet boundary conditions.
摘要翻译： 公开了一种用于从医学图像数据（如磁共振成像（MRI））数据进行主动脉缩窄的非侵入性血流动力学评估的方法和系统。 从患者的医学图像数据估计主动脉和超主动脉血管的患者特异性内腔解剖结构，例如对比度增强的MRI。 根据患者的医学图像数据估计患者特异性主动脉血流速率，例如速度编码的相位对比MRI电影图像。 基于患者特异性内腔解剖，患者特异性主动脉血流速率和患者的非侵入性临床测量，计算主动脉血流计算模型的患者特异性入口和出口边界条件。 使用主动脉血流计算模型和患者特定的入口和出口边界条件，计算患者特异性内腔解剖结构的主动脉血流和压力。
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2.发明申请Method and System for Hemodynamic Assessment of Aortic Coarctation from Medical Image Data 有权医学图像数据主动脉缩窄血流动力学评估方法与系统公开(公告)号：US20130243294A1
公开(公告)日：2013-09-19
申请号：US13826307
申请日：2013-03-14
申请人： Kristof Ralovich , Lucian Mihai Itu , Viorel Mihalef , Puneet Sharma , Razvan Ioan Ionasec , Dime Vitanovski , Waldemar Krawtschuk , Dorin Comaniciu
发明人： Kristof Ralovich , Lucian Mihai Itu , Viorel Mihalef , Puneet Sharma , Razvan Ioan Ionasec , Dime Vitanovski , Waldemar Krawtschuk , Dorin Comaniciu
IPC分类号： G06T7/00
CPC分类号： G06T7/0012 , G06T2207/10076 , G06T2207/10096 , G06T2207/30104
摘要： A method and system for non-invasive hemodynamic assessment of aortic coarctation from medical image data, such as magnetic resonance imaging (MRI) data is disclosed. Patient-specific lumen anatomy of the aorta and supra-aortic arteries is estimated from medical image data of a patient, such as contrast enhanced MRI. Patient-specific aortic blood flow rates are estimated from the medical image data of the patient, such as velocity encoded phase-contrasted MRI cine images. Patient-specific inlet and outlet boundary conditions for a computational model of aortic blood flow are calculated based on the patient-specific lumen anatomy, the patient-specific aortic blood flow rates, and non-invasive clinical measurements of the patient. Aortic blood flow and pressure are computed over the patient-specific lumen anatomy using the computational model of aortic blood flow and the patient-specific inlet and outlet boundary conditions.
摘要翻译： 公开了一种用于从医学图像数据（如磁共振成像（MRI））数据进行主动脉缩窄的非侵入性血流动力学评估的方法和系统。 从患者的医学图像数据估计主动脉和超主动脉血管的患者特异性内腔解剖结构，例如对比度增强的MRI。 根据患者的医学图像数据估计患者特异性主动脉血流速率，例如速度编码的相位对比MRI电影图像。 基于患者特异性内腔解剖，患者特异性主动脉血流速率和患者的非侵入性临床测量，计算主动脉血流计算模型的患者特异性入口和出口边界条件。 使用主动脉血流计算模型和患者特定的入口和出口边界条件，计算患者特异性内腔解剖结构的主动脉血流和压力。
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公开(公告)号：US20110243407A1
公开(公告)日：2011-10-06
申请号：US13080891
申请日：2011-04-06
申请人： Michal Sofka , Kristof Ralovich , Jingdan Zhang , Shaohua Kevin Zhou , Gianluca Paladini , Dorin Comaniciu
发明人： Michal Sofka , Kristof Ralovich , Jingdan Zhang , Shaohua Kevin Zhou , Gianluca Paladini , Dorin Comaniciu
CPC分类号： G06K9/6256 , G06F19/00 , G06F19/321 , G06T7/0012 , G06T2200/16 , G06T2207/20016
摘要： For cloud-based computer assisted detection, hierarchal detection is used, allowing detection on data at progressively greater resolutions. Detected locations at coarser resolutions are used to limit the data transmitted at greater resolutions. Data is only transmitted for neighborhoods around the previously detected locations. Subsequent detection using higher resolution data refines the locations, but only for regions associated with previous detection. By limiting the number and/or size of regions provided at greater resolutions based on the previous detection, the progressive transmission avoids transmission of some data. Additionally, or alternatively, lossy compression may be used without or with minimal reduction in detection sensitivity.
摘要翻译： 对于基于云的计算机辅助检测，使用层次检测，允许以逐渐更大的分辨率检测数据。 较粗分辨率下的检测位置用于限制以更高分辨率传输的数据。 仅针对先前检测到的位置周围的邻域发送数据。 使用较高分辨率数据的后续检测会优化位置，但仅适用于与先前检测相关的区域。 通过基于先前的检测限制以更大分辨率提供的区域的数量和/或尺寸，逐行传输避免了一些数据的传输。 另外或者可选地，可以使用有损压缩，而不用或以最小的检测灵敏度降低。
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公开(公告)号：US08811697B2
公开(公告)日：2014-08-19
申请号：US13080891
申请日：2011-04-06
申请人： Michal Sofka , Kristof Ralovich , Jingdan Zhang , Shaohua Kevin Zhou , Gianluca Paladini , Dorin Comaniciu
发明人： Michal Sofka , Kristof Ralovich , Jingdan Zhang , Shaohua Kevin Zhou , Gianluca Paladini , Dorin Comaniciu
CPC分类号： G06K9/6256 , G06F19/00 , G06F19/321 , G06T7/0012 , G06T2200/16 , G06T2207/20016
摘要： For cloud-based computer assisted detection, hierarchal detection is used, allowing detection on data at progressively greater resolutions. Detected locations at coarser resolutions are used to limit the data transmitted at greater resolutions. Data is only transmitted for neighborhoods around the previously detected locations. Subsequent detection using higher resolution data refines the locations, but only for regions associated with previous detection. By limiting the number and/or size of regions provided at greater resolutions based on the previous detection, the progressive transmission avoids transmission of some data. Additionally, or alternatively, lossy compression may be used without or with minimal reduction in detection sensitivity.
摘要翻译： 对于基于云的计算机辅助检测，使用层次检测，允许以逐渐更大的分辨率检测数据。 较粗分辨率下的检测位置用于限制以更高分辨率传输的数据。 仅针对先前检测到的位置周围的邻域发送数据。 使用较高分辨率数据的后续检测会优化位置，但仅适用于与先前检测相关的区域。 通过基于先前的检测限制以更大分辨率提供的区域的数量和/或尺寸，逐行传输避免了一些数据的传输。 另外或者可选地，可以使用有损压缩，而不用或以最小的检测灵敏度降低。
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