Covidien LP

Coviden LP

Superdimension, Ltd.

Covidien Kp

Oren P Weingarten

Ron Barak

Dorian Averbuch

Ariel Birenbaum

Eyal Klein

Guy Alexandroni

Evgeni Kopel

Alexander Y Nepomniashchy

Benjamin Greenburg

Oded Zur

Andrew E Brown

Nicolas J Merlet

Dafna Mardix

Efrat Kedmi-Shahar

Ran Cohen

Lev Abramovich Koyrakh

Igor A Markov

Elad D Lachmanovich

Leo Joskowicz

David Miel

Nathan Knutson

Michael E Calcutt

Ivan Vorobeychyk

Matthew W Baker

Jiguang Shen

Israel Kehat

Irina Shevlev

Ofer Barasofsky

Tatyana Shpiner

Alexander Nepomniashchy

Igor Markov

Devices, systems, methods, and computer-readable media for registering an electromagnetic registration of a luminal network to a 3D model of the luminal network include accessing a 3D model of a luminal network based on computed tomographic (CT) images of the luminal network, selecting a plurality of reference points within the 3D model of the luminal network, obtaining a plurality of survey points within the luminal network, dividing the 3D model of the luminal network and the luminal network into a plurality of regions, assigning a plurality of weights to the plurality of regions, determining an alignment of the plurality of reference points with the plurality of survey points based on the plurality of weights, and generating a registration based on the alignment, the registration enabling conversion of the plurality of survey points within the luminal network to points within the 3D model of the luminal network.

Multi-rigid registration of magnetic navigation to a computed tomography volume

Imaging systems and methods estimate poses of a fluoroscopic imaging device, which may be used to reconstruct 3D volumetric data of a target area, based on a sequence of fluoroscopic images of a medical device or points, e.g., radiopaque markers, on the medical device captured by performing a fluoroscopic sweep. The systems and methods may identify and track the points along a length of the medical device appearing in the captured fluoroscopic images. The 3D coordinates of the points may be obtained, for example, from electromagnetic sensors or by performing a structure from motion method on the captured fluoroscopic images. In other aspects, a 3D shape of the catheter is determined, then the angle at which the 3D catheter projects onto the 2D catheter in each captured fluoroscopic image is found.

Systems and methods for pose estimation of a fluoroscopic imaging device and for three-dimensional imaging of body structures

Surgical guidance systems and methods visually mark a structure of interest (SOI) of an organ on intraoperative images captured by a locatable imaging device. A location of the SOI relative to a body structure (e.g., a passageway system) associated with the organ is determined in a preoperative image that is captured by a medical diagnostic imaging (MDI) system. The location of the SOI relative to the body structure in the preoperative image is then mapped onto a reconstructed version of the body structure based on location information provided by localization sensors distributed on the body structure. An intraoperative image taken by the locatable imaging device is aligned with the reconstructed version of the body structure and an image object representing the SOI is overlaid on the intraoperative image at a location that is mapped from the reconstructed version of the body structure.

Systems and methods for providing surgical guidance

A system for registering a luminal network to a 3D model of the luminal network includes a computing device configured to identify potential matches in the 3D model with location data of a location sensor, assigning one of the potential matches a registration score based on a deformation model applied to the 3D model, and displaying the potential match having the highest registration score.

Deformable registration of computer-generated airway models to airway trees

A method of performing a surgical procedure includes obtaining images of a patient's anatomy using a cone beam computed tomography machine while the patient is sedated, identifying an area of interest in the images obtained by the cone beam computed tomography machine, identifying a pathway to the identified area of interest using the images obtained by the cone beam computed tomography machine, and navigating a catheter within the patient's airways to the identified area of interest using the identified pathway.

Cone beam computed tomography integration for creating a navigation pathway to a target in the lung and method of navigating to the target

A method and system implementing a method for detecting a catheter in fluoroscopic data and updating a displayed electromagnetic position of the catheter on a 3D rendering is provided including navigating a catheter to a target area and acquiring fluoroscopic data from a fluoroscopic sweep of the target area. An initial catheter detection is performed to detect catheter tip candidates in each 2D frame of the fluoroscopic data using a shallow neural network. A secondary catheter detection is performed to detect catheter tip candidates in each 2D frame of the fluoroscopic data using a deep neural network. False-positive catheter tip candidates are removed by reconstructing a 3D position of the catheter tip and finding an intersecting point of rays corresponding to each 2D frame.

System and method for catheter detection in fluoroscopic images and updating displayed position of catheter

A method and system for reducing divergence between computed tomography images and a patient using three-dimensional reconstructions. The method utilizes cone beam imaging or three-dimensional fluoroscopy to supplement or supplant pre-operative computed tomography imaging.

Cone beam and 3D fluoroscope lung navigation

Systems, methods, and computer-readable media for registering initial computed tomography (CT) images of a luminal network with subsequent CT images of the luminal network include obtaining initial CT images of the luminal network and subsequent CT images of the luminal network, generating an initial three-dimensional (3D) model of the luminal network based on the initial CT images of the luminal network, generating a subsequent 3D model of the luminal network based on the subsequent CT images of the luminal network, and matching the initial 3D model with the subsequent 3D model based on a registration.

Systems, methods, and computer-readable media for automatic computed tomography to computed tomography registration

A method and system for facilitating identification and marking of a target in a displayed Fluoroscopic Three-Dimensional Reconstruction (F3DR) of a body region of a patient. The system includes a display and a storage device storing instructions for receiving an initial selection of the target in the F3DR, fining the F3DR based on the initial selection of the target, displaying the fined F3DR on the display, and receiving a final selection of the target in the fined F3DR via a user selection. The system further includes at least one hardware processor configured to execute said instructions. The method and instructions may also include receiving a selection of a medical device in two two-dimensional fluoroscopic images, where the medical device is located in an area of the target, and initially fining the F3DR based on the selection of the medical device.

System and method for identifying and marking a target in a fluoroscopic three-dimensional reconstruction

A system and method for registration of a pre-procedural image data set (e.g. CT data) or a 3D model derived therefrom with a patient's luminal structure (e.g., airways in the lungs) using intraprocedural fluoroscopic imaging techniques.

Systems and methods of fluoro-CT imaging for initial registration

Systems and methods of estimating movement of anatomical structures of a new patient include learning one or more deformation models from preoperative and intraoperative imaging data of a set of other patients and estimating movement of anatomical structures of the new patient based on the one or more deformation models and preoperative imaging data of the new patient. Estimating movement of the anatomical structures may include applying deformation models to map data derived from preoperative imaging data of a new patient to obtain deformed map data for each deformation model, and determining the deformation model that best fits the intraoperative imaging data of the new patient. Applying a deformation model to map data may include applying a transformation to the deformation model and interpolating to obtain a deformed map data. Registration is computed between locations of a medical device sampled during navigation of the medical device through the new patient and the original and deformed map data. The map data which fits the 3D locations the best is applied to the targets of the new patient.

Systems and methods for estimating the movement of a target using a universal deformation model for anatomic tissue

Methods, systems, and computer-readable media for registering electromagnetic navigation data of a luminal network to a 3D model of the luminal network includes accessing a 3D model of a luminal network based on computed tomographic (CT) images of the luminal network, the 3D model corresponding to a CT coordinate space, selecting a plurality of reference points within the 3D model of the luminal network, accessing a plurality of survey points within the luminal network, the plurality of survey points being based on electromagnetic navigation data and corresponding to a body coordinate space, correlating the plurality of reference points and the plurality of survey points to determine pairs of correlated reference points and survey points; and deriving a transformation that maps the body coordinate space to the CT coordinate space based on the pairs of correlated reference points and survey points.

Systems, methods, and computer-readable media for non-rigid registration of electromagnetic navigation space to CT volume

A system for constructing fluoroscopic-based three-dimensional volumetric data of a target area within a patient from two-dimensional fluoroscopic images including a structure of markers, a fluoroscopic imaging device configured to acquire a sequence of images of the target area and of the structure of markers, and a computing device. The computing device is configured to estimate a pose of the fluoroscopic imaging device for at least a plurality of images of the sequence of images based on detection of a possible and most probable projection of the structure of markers as a whole on each image of the plurality of images. The computing device is further configured to construct fluoroscopic-based three-dimensional volumetric data of the target area based on the estimated poses of the fluoroscopic imaging device.

System and method for local three dimensional volume reconstruction using a standard fluoroscope

A flexible catheter includes an elongated body, a first monolithic wire, and a second monolithic wire. The first monolithic wire forms a first sensor that is disposed in the distal end portion of the elongated body. The first sensor is configured to detect the position of a distal end of the elongated body within anatomy of a patient. The second monolithic wire forms a second sensor that is disposed in the distal end portion of the elongated body a known distance from the first sensor. The first and second sensors are configured to determine the position of the distal end portion within six degrees-of-freedom. A method of manufacturing the flexible catheter is also provided.

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Herzliya, Israel

Oren P Weingarten