Siemens Aktiengesellschaft

Siemens Medical Solutions Usa, Inc.

Mako Surgical Corporation

Siemens Healthcare Gmbh

Siemens Corporation

Duerr Dental Ag

Piur Imaging Gmbh

White Lion Technologies Ag

Imfusion Gmbh

Wolfgang Wein

Ali Kamen

Raphael Prevost

José Luis Moctezuma De La Barrera

Mehrdad Salehi

Bernhard Geiger

Berthold Kiefer

Matthias John

Chenyang Xu

Christophe Chefd'hotel

Ralf Nanke

Estelle Camus

Ali Khamene

Jens Fehre

Martin Requardt

Jens Guehring

Sebastian Vogt

Hari Sundar

Clifford R Weiss

Mamadou Diallo

Parmeshwar Khurd

Martin Haidacher

Robert Bauer

Christophe Duong

Michael Burns

Frederik Bender

Alexander Ladikos

Razvan Chisu

Julian Sprung

Systems and methods for calibrating ultrasound imaging directed towards a bone region. An ultrasound imaging device generates a first steered frame and a second steered frame, wherein the first steered frame and the second steered frame are directed towards the bone region at different angles from one another and are superimposed with one another. Parameters of each of the first steered frame and the second steered frame are applied to a cost function that outputs an estimated propagation speed of ultrasound waves to the bone region for optimizing an appearance of the first steered frame and the second steered frame. The ultrasound imaging device is calibrated based on the estimated propagation speed.

Ultrasound bone registration with learning-based segmentation and sound speed calibration

A workflow is disclosed to accurately register ultrasound imaging to co-modality imaging. The ultrasound imaging is segmented with a convolutional neural network to detect a surface of the object. The ultrasound imaging is calibrated to reflect a variation in propagation speed of the ultrasound waves through the object by minimizing a cost function that sums the differences between the first and second steered frames, and compares the first and second steered frames of the ultrasound imaging with a third frame of the ultrasound imaging that is angled between the first and second steered frames. The ultrasound imaging is temporarily calibrated with respect to a tracking coordinate system by creating a point cloud of the surface and calculating a set of projection values of the point cloud to a vector. The ultrasound imaging, segmented and calibrated, is automatically registered to the co-modality imagine.

A method of determining a three-dimensional motion of a movable ultrasound probe () is described. The method is carried out during acquisition of an ultrasound image of a volume portion () by the ultrasound probe. The method comprises receiving a stream of ultrasound image data () from the ultrasound probe () while the ultrasound probe is moved along the volume portion (); inputting at least a sub-set of the ultrasound image data () representing a plurality of ultrasound image frames () into a machine-learning module (), wherein the machine learning module () has been trained to determine the relative three-dimensional motion between ultrasound image frames (); and determining, by the machine-learning module (), a three-dimensional motion indicator () indicating the relative three-dimensional motion between the ultrasound image frames.

Apparatus and method for determining motion of an ultrasound probe

In a method for image guided prostate cancer needle biopsy, a first registration is performed to match a first image of a prostate to a second image of the prostate. Third images of the prostate are acquired and compounded into a three-dimensional (3D) image. The prostate in the compounded 3D image is segmented to show its border. A second registration and then a third registration different from the second registration is performed on distance maps generated from the prostate borders of the first image and the compounded 3D image, wherein the first and second registrations are based on a biomechanical property of the prostate. A region of interest in the first image is mapped to the compounded 3D image or a fourth image of the prostate acquired with the second modality.

System and method for image guided prostate cancer needle biopsy

A method for reconstruction of a 3D volume from a set of projection images recorded by a tomography apparatus using penetrating radiation in the field of dental medical applications takes into account a given value of at least one parameter. Simulated projection images are generated which correspond to at least a subset of the recorded projection images by simulating a projection of the penetrating radiation through the reconstructed 3D volume taking into account said given value of the at least one parameter. A re-projection error is determined by comparing the simulated projection images (with the corresponding recorded projection images. The re-projection error is then minimized by changing the value of the at least one parameter and by iterating over the above steps.

Method and tomography apparatus for reconstruction of a 3D volume

A method for registration of ultrasound device in three dimensions to a C-arm scan, the method including acquiring a baseline volume, acquiring images in which the ultrasound device is disposed, locating the device within the images, registering the location of the device to the baseline volume, acquiring an ultrasound volume from the ultrasound device, registering the ultrasound volume to the baseline volume, and performing fusion imaging to display a view of the ultrasound device in the baseline volume.

Fusion of 3D volumes with CT reconstruction

A method for registering 2-dimensional (2D) images with 3-dimensional (3D) images includes receiving a 2D reference image and a 3D moving image, initializing a registration parameter matrix that rigidly transforms the domain of the moving image, randomly sampling a set of registration parameter matrices in a neighborhood of the initial registration parameters, estimating a cost function for each of the randomly sampled parameter matrices, calculating a distance from each randomly sampled parameter matrix to the initial registration parameter matrix, calculating a mean shift vector from the estimated cost functions and distance, and updating the initial registration parameter matrix from the mean shift vector.

System and method for robust 2D-3D image registration

A method of determining a three-dimensional (3D) position of a catheter tip includes: compensating a 2D position of the tip of the catheter for respiratory motion to generate a compensated 2D catheter position, generating weighted sample points around the compensated 2D catheter position, determining correspondent points of the weighted sample points in a 3D image, computing a weighted mean and a weighted covariance of each correspondent point, and determining the 3D position of the catheter tip in the 3D image from a fusion of the weighted means and weighted covariances.

Method for dynamic road mapping

A method for visualizing one or more objects of interest within a volume of imaging data includes the steps of receiving a volume of imaging data and displaying the one or more objects of interest within the volume by adaptively changing the amount of information displayed from the volume based on (1) a viewing direction of the volume, (2) a position of the one or more objects of interest within the volume, and (3) importance values of materials within the volume.

Feature emphasis and contextual cutaways for image visualization

Exemplary systems and methods for performing registration applications are provided. An exemplary system includes a central processing unit (CPU) for transferring a plurality of images to a graphics processing unit (GPU); wherein the GPU performs a registration application on the plurality of images to produce a registration result, and wherein the GPU returns the registration result to the CPU. An exemplary method includes the steps of transferring a plurality of images from a central processing unit (CPU) to a graphics processing unit (GPU); performing a registration application on the plurality of images using the GPU; transferring the result of the step of performing from the GPU to CPU.

GPU-based image manipulation method for registration applications

Growing community of inventors

Munich, Germany

Wolfgang Wein