Abstract: Methods and systems are described which allow a classification of first and second objects in an X-ray projection image. A respective representation and localization of both objects are determined by applying the models to match the objects in the X-ray image and a spatial relation of the classified objects is obtained. Such methods and systems take advantage of artificial intelligence.

Abstract: Method and apparatus are provided for assisting with bone fracture detection. In particular, image data of a medical image is received in a processing unit from a device, which may be an imaging device, a data detection device or an image storage device. A bone structure is identified in the medical image. A fracture line in the identified bone structure is determined. A bone feature, which may include a portion of an outline of the identified bone structure, a point of the fracture line on an outline of the identified bone structure, a relative displacement of bone parts of the identified bone structure, or a combination thereof is detected. The bone feature may be classified and a corresponding output generated.

Abstract: Systems and methods are provided for image guided surgery. Such systems and methods receive a model of an anatomical structure as well as a model of an object, and process a projection image generated by an imaging device from an imaging direction, wherein the projection image includes at least a part of the anatomical structure and at least a part of the object. Based on (i) the projection image, (ii) the imaging direction, (iii) the model of the object, and (iv) the model of the anatomical structure, the systems and methods determine a spatial position and orientation of the object relative to a space of movement. The space of movement may be defined in relation to the anatomical structure.

Abstract: Systems and methods for autonomous robotic surgery are provided to control a movement of a robotic device so as to perform a surgical procedural step, wherein controlling of the movement is based on information including a spatial position and orientation of at least a part of the robotic device. A trigger information may cause the system to pause or stop the surgical procedural step and cause the system to receive a projection image. Further, the projection image may be processed so as to determine a spatial position and orientation of at least the part of the object or of the robotic device.

Abstract: Method and apparatus are provided for assisting with bone fracture detection. In particular, image data of a medical image is received in a processing unit from a device, which may be an imaging device, a data detection device or an image storage device. A bone structure is identified in the medical image. A fracture line in the identified bone structure is determined. A bone feature, which may include a portion of an outline of the identified bone structure, a point of the fracture line on an outline of the identified bone structure, a relative displacement of bone parts of the identified bone structure, or a combination thereof is detected. The bone feature may be classified and a corresponding output generated.

Abstract: Based on deep neural net and possible on an active shape model approach, an outline of an anatomy may be at least partially determined and classified. Based on certain features, an algorithm may assess whether the viewing angle of the C-arm is sufficient or not. In a further step, an algorithm may estimate how far away from the desired viewing angle the current viewing angle is and may provide guidance on how to adjust the c-arm position to reach the desired viewing angle.

Abstract: Systems and methods are provided for a continual automatic registration of bone or bone-fragments, instruments, and implants based on only one additional X-ray without the need of changing the position of the X-ray source. A two-dimensional X-ray image is received, which X-ray image shows a surgical region of interest. Artificial intelligence assisted automatic detection and localization of objects such as bone or bone-fragments, tools (e.g., a drill) and/or implants combined with a priori information about the surgical procedure are used to compute their relative three-dimensional positions and orientations at any desired point in time. This registration of the objects can be repeated multiple times and can thus provide guidance in near real time.

Abstract: Method and apparatus are provided for assisting with bone fracture detection. In particular, image data of a medical image is received in a processing unit from a device, which may be an imaging device, a data detection device or an image storage device. A bone structure is identified in the medical image. A fracture line in the identified bone structure is determined. A bone feature, which may include a portion of an outline of the identified bone structure, a point of the fracture line on an outline of the identified bone structure, a relative displacement of bone parts of the identified bone structure, or a combination thereof is detected. The bone feature may be classified and a corresponding output generated.

Abstract: Systems and methods are provided for determining an implantation curve or path, along which an implant such as a nail or a screw may be inserted and implanted into a bone, and/or to determine an entry point, which is the point at which the surgeon opens the bone for inserting the implant. According to the invention, a 2D X-ray image is received, which X-ray image shows a surgical region of interest. In that X-ray image, a first point associated with a structure of interest as well as an implantation path within the bone for an implant intended to be implanted may be determined. An entry point for an insertion of the implant into the bone is located on the implantation path. It is noted that the first point may not be the entry point.

Abstract: The outline of a bone or at least a portion thereof may be determined based on deep neural net and optionally on an active shape model approach. An algorithm may detect a fracture of the bone. An algorithm may also classify the bone fracture and provide guidance on how to treat the fracture.

Abstract: Systems and methods of processing X-ray images are provided. For example, a first X-ray image showing a first part of an object, wherein the first X-ray image is generated with a first imaging direction and with a first position of an X-ray source relative to the object, and a second image showing a second part of the object are received, wherein the second X-ray image is generated with a second imaging direction and with a second position of the X-ray source relative to the object. Further, a model of the object is received. Based on the model and taking into account at least one condition, the X-ray images are registered, wherein the condition may be one point with a fixed 3D position relative to the object, a part of a further object with a fixed 3D position relative to the object, and/or another part of the object being detectable in the X-ray images.

Abstract: A system with a processing unit for processing X-ray images may be utilized for assisting in humerus surgery based on X-ray images. Firstly, at least two X-ray images are received having been generated with different imaging directions and showing a proximal portion of a humerus. Then, (i) the X-ray images are registered, (ii) an approximation of at least a part of the 2D outline of the humerus head in both images is determined, (iii) a 3D approximation of the humerus head based on the approximated 2D outlines and the registered images is determined, and (iv) 2D image coordinates of a total of at least three different points in the X-ray images are determined. Finally, an approximation of an anatomical neck is determined as a curve on the 3D approximation of the humerus head based on the at least three determined points.

Abstract: Systems and methods are provided for processing X-ray images, wherein the methods are implemented as a software program product executable on a processing unit of the systems. Generally, an X-ray image is received by the system, the X-ray image being a projection image of a first object and a second object. The first and second objects are classified and a respective 3D model of the objects is received. At the first object, a geometrical aspect like an axis or a line is determined, and at the second object, another geometrical aspect like a point is determined. Finally, a spatial relation between the first object and the second object is determined based on a 3D model of the first object, a 3D model of the second object, and the information that the point of the second object is located on the geometrical aspect of the first object.

Abstract: Methods and systems are described which allow a classification of first and second objects in an X-ray projection image. A respective representation and localization of both objects are determined by applying the models to match the objects in the X-ray image and a spatial relation of the classified objects is obtained. Such methods and systems take advantage of artificial intelligence.

Abstract: Supported by artificial intelligence, an object is classified in an X-ray projection image. A 3D representation as well as a localization of the classified object can be determined by matching a model of the classified object to a visualization of the classified object in the X-ray image.

Abstract: The outline of a bone or at least a portion thereof may be determined based on deep neural net and optionally on an active shape model approach. An algorithm may detect a fracture of the bone. An algorithm may also classify the bone fracture and provide guidance on how to treat the fracture.

Abstract: Method and system for determining the angle of anteversion of for example bone fragments of a fractured bone are disclosed. Supported by artificial intelligence, a first object is classified in a first X-ray projection image. A a second object is classified in a second X-ray projection image. A spatial arrangement of the objects relative to each other can be determined based on a respective determination of a representation and a localization of both objects.

Abstract: Based on deep neural net and possibly on an active shape model approach, the complete outline of an anatomy may be determined and classified. Based on certain features, an algorithm may assess whether the viewing angle of the C-arm is sufficient or not. In a further step, an algorithm may estimate how far away from the desired viewing angle the current viewing angle is and may provide guidance on how to adjust the c-arm position to reach the desired viewing angle.

Abstract: Systems and methods are provided for processing X-ray images, wherein the methods are implemented as a software program product executable on a processing unit of the systems. Generally, an X-ray image is received by the system, the X-ray image being a projection image of a first object and a second object. The first and second objects are classified, and a respective 3D model of the objects is received. At the first object, a geometrical aspect like an axis or a line is determined, and at the second object, another geometrical aspect like a point is determined. Finally, a spatial relation between the first object and the second object is determined based on a 3D model of the first object, a 3D model of the second object, and the information that the point of the second object is located on the geometrical aspect of the first object.