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公开(公告)号：US20150366532A1
公开(公告)日：2015-12-24
申请号：US14735203
申请日：2015-06-10
发明人： Ingmar Voigt , Tommaso Mansi , Bogdan Georgescu , Helene C Houle , Dorin Comaniciu , Codruta-Xenia Ene , Mihai Scutaru
CPC分类号： A61B8/065 , A61B8/0883 , A61B8/12 , A61B8/14 , A61B8/463 , A61B8/488 , A61B8/5223 , A61B8/5238 , G06T7/0012 , G06T19/00 , G06T2207/10132 , G06T2207/20081 , G06T2207/30048 , G06T2210/41
摘要： A regurgitant orifice of a valve is detected. The valve is detected from ultrasound data. An anatomical model of the valve is fit to the ultrasound data. This anatomical model may be used in various ways to assist in valvular assessment. The model may define anatomical locations about which data is sampled for quantification. The model may assist in detection of the regurgitant orifice using both B-mode and color Doppler flow data with visualization without the jet. Segmentation of a regurgitant jet for the orifice may be constrained by the model. Dynamic information may be determined based on the modeling of the valve over time.
摘要翻译： 检测到阀的反流孔。 从超声数据中检测瓣膜。 瓣膜的解剖模型符合超声数据。 这种解剖模型可以以各种方式用于辅助瓣膜评估。 该模型可以定义关于数据被采样以进行定量的解剖位置。 该模型可以帮助检测回流孔，使用B模式和彩色多普勒流量数据，而无需喷射。 用于孔口的反流喷射器的分段可能受到模型的限制。 动态信息可以基于阀随时间的建模来确定。
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公开(公告)号：US10271817B2
公开(公告)日：2019-04-30
申请号：US14735203
申请日：2015-06-10
发明人： Ingmar Voigt , Tommaso Mansi , Bogdan Georgescu , Helene C Houle , Dorin Comaniciu , Codruta-Xenia Ene , Mihai Scutaru
摘要： A regurgitant orifice of a valve is detected. The valve is detected from ultrasound data. An anatomical model of the valve is fit to the ultrasound data. This anatomical model may be used in various ways to assist in valvular assessment. The model may define anatomical locations about which data is sampled for quantification. The model may assist in detection of the regurgitant orifice using both B-mode and color Doppler flow data with visualization without the jet. Segmentation of a regurgitant jet for the orifice may be constrained by the model. Dynamic information may be determined based on the modeling of the valve over time.
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公开(公告)号：US20170116748A1
公开(公告)日：2017-04-27
申请号：US15317353
申请日：2015-06-08
发明人： Mihai Scutaru , Ingmar Voigt , Tommaso Mansi , Razvan Ionasec , Helene C. Houle , Anand Vinod Tatpati , Dorin Comaniciu
CPC分类号： G06T7/143 , G06K9/6249 , G06K9/6256 , G06K9/6267 , G06K9/6297 , G06K2209/051 , G06T7/0012 , G06T7/0016 , G06T7/11 , G06T7/174 , G06T2207/10132 , G06T2207/20076 , G06T2207/20081 , G06T2207/20132 , G06T2207/20164 , G06T2207/30048 , G06T2210/12
摘要： Anatomy, such as papillary muscle, is automatically detected (34) and/or detected in real-time. For automatic detection (34) of small anatomy, machine-learnt classification with spatial (32) and temporal (e.g., Markov) (34) constraints is used. For real-time detection, sparse machine-learnt detection (34) interleaved with optical flow tracking (38) is used.
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