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Bolus tracking from pulsed x-ray projections: A feasibility study using a five-dimensional cardiac CT contrast dynamics model.

Autor: Haneda E; GE HealthCare Technology and Innovation Center, Niskayuna, New York, USA., Heukensfeldt Jansen IM; GE HealthCare Technology and Innovation Center, Niskayuna, New York, USA., Wu P; GE HealthCare Technology and Innovation Center, Niskayuna, New York, USA., Pack JD; GE HealthCare Technology and Innovation Center, Niskayuna, New York, USA., Hsiao A; Department of Radiology at University of California San Diego, La Jolla, California, USA., McVeigh E; Departments of Bioengineering, Cardiology and Radiology at University of California San Diego, La Jolla, California, USA., De Man B; GE HealthCare Technology and Innovation Center, Niskayuna, New York, USA.

Publikováno v: Medical physics [Med Phys] 2024 Oct 16. Date of Electronic Publication: 2024 Oct 16.

Motion correction of wide-detector 4DCT images for cardiac resynchronization therapy planning.

Autor: Manohar A; Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Radiology, Stanford University, Stanford, CA, USA; Cardiovascular Institute, Stanford University, Stanford, CA, USA., Yang J; Department of Bioengineering, University of California San Diego, La Jolla, CA, USA., Pack JD; Radiation Systems Lab, GE Global Research, Niskayuna, New York, USA., Ho G; Department of Medicine, Division of Cardiology, University of California San Diego, La Jolla, CA, USA., McVeigh ER; Department of Bioengineering, University of California San Diego, La Jolla, CA, USA; Department of Medicine, Division of Cardiology, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA. Electronic address: emcveigh@ucsd.edu.

Publikováno v: Journal of cardiovascular computed tomography [J Cardiovasc Comput Tomogr] 2024 Mar-Apr; Vol. 18 (2), pp. 170-178. Date of Electronic Publication: 2024 Jan 11.

High-Speed On-Site Deep Learning-Based FFR-CT Algorithm: Evaluation Using Invasive Angiography as the Reference Standard.

Autor: Giannopoulos AA; Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Ramistrasse 100, Zurich 8091, Switzerland., Keller L; Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Ramistrasse 100, Zurich 8091, Switzerland., Sepulcri D; Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Ramistrasse 100, Zurich 8091, Switzerland., Boehm R; Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Ramistrasse 100, Zurich 8091, Switzerland., Garefa C; Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Ramistrasse 100, Zurich 8091, Switzerland., Venugopal P; GE Research, Schenectady, NY., Mitra J; GE Research, Schenectady, NY., Ghose S; GE Research, Schenectady, NY., Deak P; GE Research, Schenectady, NY., Pack JD; GE Research, Schenectady, NY., Davis CL; GE Research, Schenectady, NY., Stähli BE; Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland., Stehli J; Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland., Pazhenkottil AP; Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Ramistrasse 100, Zurich 8091, Switzerland., Kaufmann PA; Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Ramistrasse 100, Zurich 8091, Switzerland., Buechel RR; Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Ramistrasse 100, Zurich 8091, Switzerland.

Publikováno v: AJR. American journal of roentgenology [AJR Am J Roentgenol] 2023 Oct; Vol. 221 (4), pp. 460-470. Date of Electronic Publication: 2023 May 03.