Sync-rx Ltd.

Vuze Medical Ltd.

Superdimension, Ltd.

Other

Synx-rx, Ltd.

Covidien LP

David Tolkowsky

Ran Cohen

Alexander Steinberg

Eldad Klaiman

Sagiv Philipp

Zohar Barzelay

Pinhas Gilboa

David Hollander

Gavriel Joseph Iddan

Yoav Stein

Danny Blecher

Jacob Blank

3D image data of a skeletal portion is acquired. While a portion of a tool is disposed at a first location along an insertion path, first and second x-rays are acquired from first and second image views. A processor registers the x-rays with the 3D image data, identifies a location of a tool within the x-rays, and computes an anticipated forward path of the tool within the 3D image data from the x-rays. The tool is moved to a second location along the insertion path and an additional x-ray is acquired from a single image view. The processor facilitates identifying if the tool has deviated from the anticipated forward path by registering the additional x-ray to the 3D image data and identifying a location of the portion of the tool within the additional x-ray. Other embodiments are also described.

Apparatus and methods for use with image-guided skeletal procedures

Apparatus and methods are described for use with an imaging device () configured to acquire a set of angiographic images of a lumen. At least one processor () includes blood-velocity-determination functionality () that determines blood velocity within the lumen, via image processing. Current-flow-related-parameter-determination functionality () determines a value of a flow-related parameter at the location based upon the determined blood velocity. Flow-related-parameter-receiving functionality () receives an indication of a value of a second flow-related parameter of the subject, and index-determination functionality () determines a value of a luminal-flow-related index of the subject at the location, by determining a relationship between the value of the current flow-related parameter and the value of the second flow-related parameter. Other applications are also described.

Determining a characteristic of a lumen by measuring velocity of a contrast agent

Apparatus and methods are described including acquiring 3D image data of a skeletal portion. While a tool that is coupled to a robot is disposed at a first location along an insertion path, two 2D x-ray images are acquired from respective views. A computer processor (i) determines the first location with respect to the 3D image data based upon identifying the first location within the 2D x-ray images and registering the 2D x-ray images to the 3D image data, and (ii) derives a relationship between the first location and a given location within the 3D image data. Subsequently, the robot moves the tool to a second location responsively to the derived relationship. The processor tracks the motion of the robot relative to the first location, derives the second location, and drives a display to display the second location. Other applications are also described.

Apparatus and methods for use with skeletal procedures

Apparatus and methods are described including a processor () configured to receive first and second sets of extraluminal images of a lumen, the second set being acquired while an endoluminal device is being moved through the lumen. The processor designates at least one of the first set of images as a roadmap image, and designates, within the lumen in the roadmap image, a roadmap pathway (). A plurality of features () that are visible within at least some of the second set of extraluminal images are identified, and an arrangement of three or more of the features within the image are compared to a shape of at least a portion of the roadmap pathway. Based upon the comparing, the identified features are mapped to locations along the roadmap pathway within the roadmap image. Other applications are also described.

Apparatus and methods for mapping a sequence of images to a roadmap image

Respective longitudinal insertion paths for two tools are planned and associated with 3D image data of a skeletal portion. While respective portions of the tools are disposed at first respective locations along their respective longitudinal insertion paths, first and second x-rays of the respective portions of the tools and the skeletal portion are acquired from respective first and second views. A computer processor matches between a tool in the first x-ray and the same tool in the second x-ray by: (A) identifying respective tool elements of each tool within the first and second x-rays, (B) registering the first and second x-rays to the 3D image data, and (C) based upon the identified respective tool elements and the registration, identifying for at least one tool element a correspondence between the tool element and the respective planned longitudinal insertion path for that tool. Other applications are also described.

3D image data of a skeletal portion is acquired. A location of a proximal portion of a tool is calculated and a location is derived of a distal portion of the tool with respect to the skeletal portion, with respect to the 3D image data. A display indicates the derived location. First and second 2D images of the distal portion of the tool are acquired from two different poses of a 2D imaging device with respect to the subject and registered with the 3D image data. The location of the distal portion with respect to the 3D image data of the skeletal portion is determined based on the registration and an identified location of the distal portion within the 2D x-rays. Based upon the determined location, the display updates the indicated location of the distal portion. Other embodiments are also described.

3D image data of a skeletal portion within a subject's body is acquired. Subsequently, one or more radiopaque elements are positioned with respect to the body and first and second x-rays of the radiopaque elements and the skeletal portion are acquired from respective views. Based upon an identified location of the radiopaque elements within the x-rays, and registration of the x-rays to the 3D image data, the location of the radiopaque elements with respect to the 3D image data is determined. An optical image of the body and the radiopaque elements is acquired and the location of the radiopaque elements within the optical image is identified. The 3D image data is overlaid upon the optical image by aligning (a) the location of the radiopaque elements within the 3D image data with (b) the location of the radiopaque elements within the optical image. Other applications are also described.

Apparatus and methods are described including acquiring 3D image data of a targeted vertebra. A processor indicates the targeted vertebra within the 3D image data. A radiopaque element is positioned on the body of the subject with respect to the spine and a radiographic image is acquired. The processor (a) generates a plurality of 2D projections of the targeted vertebra from the 3D image data, (b) for each vertebra that is visible in the radiographic image, identifies if there exists a 2D projection of the targeted vertebra that matches the radiographic image of the vertebra that is visible, and (c) in response, indicates on the 2D radiographic image the vertebra for which a match with a projection of the targeted vertebra was identified, such that a location of the targeted vertebra is identified with respect to the radiopaque element. Other applications are also described.

Apparatus and methods are described including acquiring 3D image data of a targeted skeletal portion within a body of a subject, and a 2D radiographic image of the targeted skeletal portion. A machine-learning engine is used to generate machine-learning data based on (i) the 3D image data of the targeted skeletal portion, (ii) a database of 2D projection images generated from the 3D image data, and (iii) respective values of one or more viewing parameters corresponding to each 2D projection image. A computer processor receives the machine-learning data, receives the 2D radiographic image of the targeted skeletal portion, and registers the 2D radiographic image to the 3D image data by using the machine-learning data to find a 2D projection from the 3D image data that matches the 2D radiographic image of the targeted skeletal portion. Other applications are also described.

Apparatus and methods are described for imaging a tool inside a portion of a subject's body that undergoes motion. A plurality of image frames are acquired of the portion of the subject's body. The image frames are image tracked by (a) automatically identifying at least a feature of the tool in at least a portion of the image frames, and (b) aligning the tool in image frames of the portion of the image frames, based on the automatic identifying. The image-tracked image frames of the portion of the subject's body are displayed as an image stream. Other embodiments are also described.

Automatic stabilization of a frames of image stream of a moving organ having intracardiac or intravascular tool in the organ that is displayed in movie format

Apparatus and methods are described for use with a plurality of angiographic image frames of a moving lumen of a subject, including aligning the image frames with each other. Using the aligned image frames, a time it takes a contrast agent to travel a known distance through the lumen is determined. At least partially in response thereto, a characteristic of the lumen is determined, and, in response to the determined characteristic, an output is generated on a display. Other applications are also described.

Apparatus and methods are described for use with an imaging device () configured to acquire a set of angiographic images of a lumen. At least one processor () determines blood velocity within the lumen, via image processing. The processor determines a value of a flow-related parameter at the location based upon the determined blood velocity. The processor additionally receives an indication of a value of a second flow-related parameter of the subject, and determines a value of a luminal-flow-related index of the subject at the location, by determining a relationship between the value of the current flow-related parameter and the value of the second flow-related parameter. Other applications are also described.

Determining a luminal-flow-related index using blood velocity determination

Apparatus and methods are described for use with an endoluminal data-acquisition device configured to be moved through a lumen of a subject's body, and a two-dimensional angiographic image of the lumen. A value of a luminal-flow-related index of the subject is determined non-invasively at a plurality of locations along the lumen, at least partially by performing image processing on the angiographic image. While the endoluminal data-acquisition device is being moved through the lumen, a set of endoluminal data points of the lumen at a plurality of locations within the lumen is acquired, using the endoluminal data-acquisition device. It is determined that respective endoluminal data points correspond to respective locations along the lumen, and, in response thereto, it is determined that respective endoluminal data points correspond to respective values of the luminal flow-related index. Other applications are also described.

Coregistration of endoluminal data points with values of a luminal-flow-related index

Apparatus for performing a procedure using a tool configured to be advanced into a skeletal portion within a body of a subject along a longitudinal insertion path, and for use with:

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Tel Aviv, Israel

David Tolkowsky