Abstract: Apparatus and methods are described including a processor (20) 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 (42). A plurality of features (44, 46, 48, 50) 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.

Abstract: Using a first imaging device, 3D image data of a skeletal portion is acquired. A second imaging device is positioned in a first position, and a starting image is generated by either, (a) generating based on the 3D image data a first 2D projection image corresponding to the first position, or (b) acquiring with the second device, from the first position, an acquired 2D image of the skeletal portion and, using a computer processor (22), registering the acquired 2D image with the 3D image data. The second device is moved to a second position, and without acquiring a 2D image with the second device from the second position, using the at least one computer processor, generating based on the 3D image data a subsequent image that is a 2D projection image that corresponds to the second position of the second device. Other embodiments are also described.

Abstract: Apparatus and methods are described including, using a computer processor, automatically identifying whether a given pixel within an image corresponds to a portion of an object. A set of concentric circles that are disposed around the pixel are sampled, and a first function is applied to each of the circles such that the circles are defined by a first set of rotationally invariant descriptors. A second function is applied to the set of circles to generate a second set of descriptors, each of which represents a difference between respective pairs of the circles. A third function is applied such that the second set of descriptors becomes rotationally invariant. The processor identifies whether the given pixel corresponds to the portion of the object, based upon the first and second sets of rotationally invariant descriptors. Other applications are also described.

Abstract: A directed energy deposition nozzle assembly including (1) a nozzle configured to dispense material for directed energy deposition, wherein the material comprises one or more of metallic powder, ceramic powder, and glass powder, and wherein (a) the nozzle has an orifice through which the material exits the nozzle, wherein the nozzle comprises an inner body and an outer body that is peripherally disposed around the inner body, and wherein the orifice is defined by a gap between the inner body and the outer body, or (b) the nozzle comprises a plurality of orifices through which the material exits the nozzle, and (2) a vibrator configured to apply a vibration to the nozzle.

Abstract: A procedure is performed with respect to a skeletal portion within a body with a tool mounted upon a steerable arm. 3D image data is acquired of the skeletal portion. First and second x-ray images of the tool and the skeletal portion are acquired from respective first and second views. A computer processor (i) registers the first and second images to the image data, (ii) identifies a location of the tool with respect to the skeletal portion, within the first and second images, (iii) determines the tool's location with respect to the image data, (iv) compares the tool's location with a designated locational element, (v) calculates the 3D difference between the tool's location and the locational element, and (vi) generates steering instructions for the arm such that the tool is moved toward the locational element. Other applications are also described.

Abstract: A procedure is performed with a tool coupled with one or more sensors. 3D image data is acquired of a skeletal portion. First and second x-ray images of the tool and the skeletal portion are acquired from respective first and second views. A computer processor (22) (i) registers the x-ray images to the image data, (ii) identifies a first location of the tool with respect to the skeletal portion, within the x-ray images, (iii) determines the tool's first location with respect to the image data, (iv) subsequently to moving the tool to a second location, obtains measurements by the sensors pertaining to the movement of the tool, (v) derives the second location of the tool with respect to image data by applying the information from the sensors to the determined first location of the tool, and (vi) generates an output. Other applications are also described.

Abstract: Apparatus and methods are described for use with a tool that is inserted into a portion of a body of a subject that undergoes cyclic motion. The apparatus and methods include using an imaging device, acquiring a plurality of images of the tool inside the portion of the body, at respective phases of the cyclic motion. Using at least one computer processor, an extent of movement of the tool with respect to the portion of the body that is due to the cyclic motion of the portion of the body is determined. In response thereto, an output is generated that is indicative of the determined extent of the movement of the tool with respect to the portion of the body. Other applications are also described.

Abstract: 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.

Abstract: A procedure is performed with respect to a skeletal portion within a body with a tool mounted upon a steerable arm. 3D image data is acquired of the skeletal portion. First and second x-ray images of the tool and the skeletal portion are acquired from respective first and second views. A computer processor (22) (i) registers the first and second images to the image data, (ii) identifies a location of the tool with respect to the skeletal portion, within the first and second images, (iii) determines the tool's location with respect to the image data, (iv) compares the tool's location with a designated locational element, (v) calculates the 3D difference between the tool's location and the locational element, and (vi) generates steering instructions for the arm such that the tool's location matches the locational element. Other applications are also described.

Abstract: Apparatus and methods are described for use with a tool that is inserted into a portion of a body of a subject that undergoes cyclic motion. The apparatus and methods include using an imaging device, acquiring a plurality of images of the tool inside the portion of the body, at respective phases of the cyclic motion. Using at least one computer processor, an extent of movement of the tool with respect to the portion of the body that is due to the cyclic motion of the portion of the body is determined. In response thereto, an output is generated that is indicative of the determined extent of the movement of the tool with respect to the portion of the body. Other applications are also described.

Abstract: 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.

Abstract: Apparatus and methods are described including a processor (20) 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 (42). A plurality of features (44, 46, 48, 50) 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.

Abstract: Apparatus and methods are described for use with an imaging device (12) configured to acquire a set of angiographic images of a lumen. At least one processor (10) includes blood-velocity-determination functionality (16) that determines blood velocity within the lumen, via image processing. Current-flow-related-parameter-determination functionality (18) determines a value of a flow-related parameter at the location based upon the determined blood velocity. Flow-related-parameter-receiving functionality (19) receives an indication of a value of a second flow-related parameter of the subject, and index-determination functionality (21) 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.

Abstract: Apparatus and methods are described including a processor (20) 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 (42). A plurality of features (44, 46, 48, 50) 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.

Abstract: 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.

Abstract: Apparatus and methods are described including, using a computer processor, automatically identifying whether a given pixel within an image corresponds to a portion of an object. A set of concentric circles that are disposed around the pixel are sampled, and a first function is applied to each of the circles such that the circles are defined by a first set of rotationally invariant descriptors. A second function is applied to the set of circles to generate a second set of descriptors, each of which represents a difference between respective pairs of the circles. A third function is applied such that the second set of descriptors becomes rotationally invariant. The processor identifies whether the given pixel corresponds to the portion of the object, based upon the first and second sets of rotationally invariant descriptors. Other applications are also described.

Abstract: Apparatus and methods are described for use with an imaging device (12) configured to acquire a set of angiographic images of a lumen. At least one processor (10) 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.

Abstract: 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.

Abstract: 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.

Abstract: With the inventive technology, wound measurement is performed, but without the patient wound, or the skin near the patient wound, needing to have an object physically placed thereon. The patient wound and patient skin near the wound are spared contact with a ruler, marker, grid, and spared the wound and area near the wound being directly physically worked-on.