A method and system is disclosed for analyzing image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. The image data may include selected overlap and be acquired with an imaging system that generates a plurality of perspectives for more than one location. An automatic system and method may then define or identify various features and/or allow for registration for alternative image data.

A method and system is disclosed for analyzing image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. The image data may include selected overlap and be acquired with an imaging system that generates a plurality of perspectives for more than one location. An automatic system and method may then define or identify various features and/or allow for registration for alternative image data.

A method and system is disclosed for analyzing image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. The image data may include selected overlap and be acquired with an imaging system that generates a plurality of perspectives for more than one location. An automatic system and method may then define or identify various features and/or allow for registration for alternative image data.

A navigated surgery system includes at least one processor that is operative to obtain a 2D medical image slice of anatomical structure of a patient. The operations further obtain a 3D graphical model of anatomical structure. The operations determine a pose of a virtual cross-sectional plane extending through the 3D graphical model of the anatomical structure that corresponds to the anatomical structure of the 2D medical image slice. The operations control the XR headset to display the 2D medical image slice of the anatomical structure of the patient, display the 3D graphical model of the anatomical structure, and display a graphical object oriented with the pose relative to the 3D graphical model of the anatomical structure.

A method for registering a two-dimensional image data set with a three-dimensional image data set of a body of interest is discloses herein. The method includes the following steps: adjusting a first virtual camera according to a distance parameter calculated corresponding to the two-dimensional image data set and the body of interest; rotating the first virtual camera according to an angle difference between a first vector and a second vector; and rotating the first virtual camera according to an angle which is corresponding to a maximum similarity value of a plurality of similarity values calculated in accordance with reconstructed images of the three-dimensional image data set which includes one generated by the first virtual camera and the others generated by other virtual cameras with different angles or different pixels from the one generated by the first virtual camera and the two-dimensional image data set.

A method for registering a two-dimensional image data set of a body of interest with a three-dimensional image data set of the body of interest is discloses herein. The method includes the following steps: generating a first reconstructed image from the three-dimensional image data set with a first spatial parameter; calculating a reference similarity value according to the first reconstructed image and the two-dimensional image data set; generating a second reconstructed image from the three-dimensional image data set with a second spatial parameter; calculating a comparison similarity value according to the second reconstructed image and the two-dimensional image data set; comparing the comparison similarity value with the reference similarity value; and registering the two-dimensional image data set to the three-dimensional image data set if the comparison similarity value is not greater than the reference similarity value.

A method for registering a two-dimensional image data set with a three-dimensional image data set of a body of interest is discloses herein. The method includes the following steps: defining a first vector of a registered virtual camera in a coordinate system of the three-dimensional image data et; obtaining a first transformed vector of an unregistered virtual camera in the coordinate system of the three-dimensional image data set by transforming the first vector of the registered virtual camera through at least one transforming matrix; defining a focal point of the unregistered virtual camera at a reference point of the two-dimensional image data set in the coordinate system of the three-dimensional image data set; and repositioning the unregistered virtual camera according to the first transformed vector and the focal point of the unregistered virtual camera.

Apparatuses, systems, and techniques to train and apply a first machine learning model to identify a plurality of regions of interest within an input image, and to train and apply a plurality of second machine learning models to identify one or more objects within each region of interest identified by the first machine learning model.

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.

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.