Siemens Healthcare Gmbh

Siemens Medical Solutions Usa, Inc.

Mihai Scutaru

Dorin Comaniciu

Bogdan Georgescu

Tommaso Mansi

Ingmar Voigt

Helene C Houle

Razvan Ionasec

Noha Youssry El-Zehiry

Anand Vinod Tatpati

Codruta-Xenia Ene

Anatomy, such as papillary muscle, is automatically detected () and/or detected in real-time. For automatic detection () of small anatomy, machine-learnt classification with spatial () and temporal (e.g., Markov) () constraints is used. For real-time detection, sparse machine-learnt detection () interleaved with optical flow tracking () is used.

Landmark detection with spatial and temporal constraints in medical imaging

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.

Valve regurgitant detection for echocardiography

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Brasov, Romania

Mihai Scutaru