Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Siemens Medical Solutions Usa, Inc.

Siemens Corporation

Siemens Aktiengesell Schaft

Xinray Systems LLC

Biosense Webster, Inc.

Jan Boese

Norbert Rahn

Dorin Comaniciu

Matthias John

Yefeng Zheng

Martin Kleen

Marcus Pfister

Günter Lauritsch

Thomas Redel

Bernhard Sandkamp

Bogdan Georgescu

Frank Dennerlein

Gareth Funka-Lea

Sasa Grbic

Rui Liao

Razvan Ioan Ionasec

Michael Maschke

Razvan Ionasec

Andreas Meyer

Benno Heigl

Peter Mountney

Alois Nöttling

Yu Deuerling-Zheng

Ali Kamen

Philipp Bernhardt

Holger Kunze

Bernhard Scholz

Ingmar Voigt

Christopher Rohkohl

Michael Zellerhoff

Klaus Klingenbeck

Mingqing Chen

Puneet Sharma

Shaohua Kevin Zhou

Lucian Mihai Itu

Saikiran Rapaka

Estelle Camus

Viorel Mihalef

Joachim Hornegger

Reinmar Killmann

Xudong Zheng

Marcus Prümmer

Kerstin Mueller

Yu Pang

Assaf Govari

Tommaso Mansi

David D Liu

Klaus Klingenbeck-Regn

Chenyang Xu

Ying Zhu

Andrew F Hall

Assaf Preiss

Peng Wang

Yanghai Tsin

Yang Wang

Andreas Maier

Klaus J Kirchberg

Wolfgang Härer

Johann Seissl

James Williams

Jens Fürst

Anja Borsdorf

Alois Noettling

Guenter Lauritsch

Frank Sprenger

Ulrich Bill

Meir Bartal

Ernst Peter Rührnschopf

Tianzhou Wang

Uwe Kirschstein

Volkmar Falk

Thomas Walther

Malte Meesmann

Jörn Justiz

Markus Kaiser

Sabine Heiland

Martin Wagner

Christian Gesell

Dominik Zaeuner

Marily Sarmiento

Methods for computing hemodynamic quantities include: (a) acquiring angiography data from a patient; (b) calculating a flow and/or calculating a change in pressure in a blood vessel of the patient based on the angiography data; and (c) computing the hemodynamic quantity based on the flow and/or the change in pressure. Systems for computing hemodynamic quantities and computer readable storage media are described.

Computation of hemodynamic quantities from angiographic data

A method and system for virtual percutaneous valve implantation is disclosed. A patient-specific anatomical model of a heart valve is estimated based on 3D cardiac medical image data and an implant model representing a valve implant is virtually deployed into the patient-specific anatomical model of the heart valve. A library of implant models, each modeling geometrical properties of a corresponding valve implant, is maintained. The implant models maintained in the library are virtually deployed into the patient specific anatomical model of the heart valve to select an implant type and size and deployment location and orientation for percutaneous valve implantation.

Method and system for virtual percutaneous valve implantation

A method and system for autoregressive model based pigtail catheter motion prediction in a fluoroscopic image sequence is disclosed. Parameters of an autoregressive model are estimated based on observed pigtail catheter tip positions in a plurality of previous frames of a fluoroscopic image sequence. A pigtail catheter tip position in a current frame of the fluoroscopic image sequence is predicted using the fitted autoregressive model. The predicted pigtail catheter tip position can be used to constrain pigtail catheter tip detection in the current frame. The predicted pigtail catheter tip position may also be used to predict abnormal motion in the fluoroscopic image sequence.

Method and system for pigtail catheter motion prediction

A method and system for fusion of multi-modal volumetric images is disclosed. A first image acquired using a first imaging modality is received. A second image acquired using a second imaging modality is received. A model and of a target anatomical structure and a transformation are jointly estimated from the first and second images. The model represents a model of the target anatomical structure in the first image and the transformation projects a model of the target anatomical structure in the second image to the model in the first image. The first and second images can be fused based on estimated transformation.

Method and system for model-based fusion of multi-modal volumetric images

A method and system for aorta segmentation in a 3D volume, such as a C-arm CT volume is disclosed. The aortic root is detected in the 3D volume using marginal space learning (MSL) based segmentation. The aortic arch is detected in the 3D volume using MSL based segmentation. The ascending aorta is tracked from the aortic root to the aortic arch in the 3D volume, and the descending aorta is tracked from the aortic arch in the 3D volume.

Method and system for automatic aorta segmentation

A method and system for registering ultrasound images and physiological models to x-ray fluoroscopy images is disclosed. A fluoroscopic image and an ultrasound image, such as a Transesophageal Echocardiography (TEE) image, are received. A 2D location of an ultrasound probe is detected in the fluoroscopic image. A 3D pose of the ultrasound probe is estimated based on the detected 2D location of the ultrasound probe in the fluoroscopic image. The ultrasound image is mapped to a 3D coordinate system of a fluoroscopic image acquisition device used to acquire the fluoroscopic image based on the estimated 3D pose of the ultrasound probe. The ultrasound image can then be projected into the fluoroscopic image using a projection matrix associated with the fluoroscopic image. A patient specific physiological model can be detected in the ultrasound image and projected into the fluoroscopic image.

Method and system for registration of ultrasound and physiological models to X-ray fluoroscopic images

A method and system for extracting a silhouette of a 3D mesh representing an anatomical structure is disclosed. The 3D mesh is projected to two dimensions. Silhouette candidate edges are generated in the projected mesh by pruning edges and mesh points based on topology analysis of the projected mesh. Each silhouette candidate edge that intersects with another edge in the projected mesh is split into two silhouette candidate edges. The silhouette is extracted using an edge following process on the silhouette candidate edges.

Method and system for efficient extraction of a silhouette of a 3D mesh

A method and system for model based fusion pre-operative image data, such as computed tomography (CT), and intra-operative C-arm CT is disclosed. A first pericardium model is segmented in the pre-operative image data and a second pericardium model is segmented in a C-arm CT volume. A deformation field is estimated between the first pericardium model and the second pericardium model. A model of a target cardiac structure, such as a heart chamber model or an aorta model, extracted from the pre-operative image data is fused with the C-arm CT volume based on the estimated deformation field between the first pericardium model and the second pericardium model. An intelligent weighted average may be used improve the model based fusion results using models of the target cardiac structure extracted from pre-operative image data of patients other than a current patient.

Method and system for pericardium based model fusion of pre-operative and intra-operative image data for cardiac interventions

The left ventricle epicardium is estimated in medical diagnostic imaging. C-arm x-ray data is used to detect an endocardium at different phases. The detected endocardium at the different phases is compared to sample endocardiums at different phases. The sample endocardiums have corresponding sample epicardiums. The transformation between the most similar sample endocardium or endocardiums over time and the detected endocardium over time is applied to the corresponding sample epicardium or epicardiums. The transformed sample epicardium over time is the estimated epicardium over time for the C-arm x-ray data.

Left ventricle epicardium estimation in medical diagnostic imaging

A tomogram of a body is provided. Projection-image data obtained by a radiation-based projection method is used for providing the tomogram. Initial voxel data are first specified for a plurality of voxels of the body. Synthetic projection-image data are generated based upon a projection rule modeling a course of the projection method. Projection-error data is determined by comparing the synthetic projection-image data with the real projection-image data. The projection-error data are imaged on the basis of a back-projection rule dependent on the projection rule so that voxel-error data are produced. Correction data is generated from the voxel-error data by a gradient-based optimizing algorithm, wherein corrected voxel data are generated using the correction data.

Computed-tomography system and method for determining volume information for a body

A method and system for model-based fusion of multi-modal volumetric images is disclosed. A first patient-specific model of an anchor anatomical structure is detected in a first medical image acquired using a first imaging modality, and a second patient-specific model of the anchor anatomical structure is detected in a second medical image acquired using a second imaging modality. A weighted mapping function is determined based on the first patient-specific model of the anchor anatomical structure and the second patient-specific model of the anchor anatomical structure using learned weights to minimize mapping error with respect to a target anatomical structure. The target anatomical structure from the first medical image to the second medical image using the weighted mapping function. In an application of this model-based fusion to transcatheter valve therapies, the trachea bifurcation is used as the anchor anatomical structure and the aortic valve is the target anatomical structure.

Method and system for model-based fusion of computed tomography and non-contrasted C-arm computed tomography

Methods, systems, and apparatus for obtaining a sequence of x-ray images are disclosed. An object of interest in a first x-ray image is detected and an area of interest, based on a predicted motion of the object of interest, is determined. A second x-ray image of the area of interest is acquired using spatial x-ray modification to control an x-ray to pass through a portion of a patient corresponding to the area of interest.

Method and system for obtaining a sequence of x-ray images using a reduced dose of ionizing radiation

A method for real-time fusion of a 2D cardiac ultrasound image with a 2D cardiac fluoroscopic image includes acquiring real time synchronized US and fluoroscopic images, detecting a surface contour of an aortic valve in the 2D cardiac ultrasound (US) image relative to an US probe, detecting a pose of the US probe in the 2D cardiac fluoroscopic image, and using pose parameters of the US probe to transform the surface contour of the aortic valve from the 2D cardiac US image to the 2D cardiac fluoroscopic image.

Image fusion for interventional guidance

A method () to compensate for cardiac and respiratory motion in cardiac imaging during minimal invasive (e.g., trans-catheter) AVI procedures by image-based tracking () on fluoroscopic images.

Method of motion compensation for trans-catheter aortic valve implantation

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Eckental, Germany

Jan Boese