A medical apparatus of embodiments includes processing circuitry. The processing circuitry is configured to input third projection data to a first trained model to generate fourth projection data, the first trained model being generated through learning using first projection data collected by a first X-ray detector included in a first scanner and relatively greatly affected by scattered rays as learning data of an input side and using second projection data relatively less affected by scattered rays as learning data of an output side, the first trained model being configured to generate, on the basis of the third projection data collected by a second X-ray detector included in a second scanner, the fourth projection data in which the influence of scattered rays in the third projection data has been reduced. The first projection data is collected by the first X-ray detector in a case where a collimator provided in a first X-ray source included in the first scanner has a first opening width. The second projection data is collected by the first X-ray detector in a case where the collimator has an opening width smaller than the first opening width.

An embodiment in accordance with the present invention provides a technique for localizing structures of interest in projection images (e.g., x-ray projection radiographs or fluoroscopy) based on structures defined in a preoperative 3D image (e.g., MR or CT). Applications include, but are not limited to, spinal interventions. The present invention achieves 3D-2D image registration (and particularly allowing use with a preoperative MR image) by segmenting the structures of interest in the preoperative 3D image and generating a simulated projection of the segmented structures to be aligned with the 2D projection image. Other applications include various clinical scenarios involving 3D-2D image registration, such as image-guided cranial neurosurgery, orthopedic surgery, biopsy, and radiation therapy.

Disclosed is a system for assisting in guiding and performing a procedure on a subject. The subject may be any appropriate subject such as inanimate object and/or an animate object. The guide and system may include various manipulable or movable members and may be registered to selected coordinate systems.

A method of assessing spinal column stability involves receiving image data corresponding to a spinal column of a patient; determining, based on the image data, a material strength of bony anatomy in at least a portion of the spinal column; completing a first stability assessment of the spinal column, based at least in part on the determined material strength; modifying the image data to simulate removal of bony anatomy or soft tissue from the spinal column to yield modified image data; and completing a second stability assessment of the spinal column, based at least in part on the determined material strength and the modified image data.

An embodiment in accordance with the present invention provides a method for 3D-2D registration (for example, registration of a 3D CT image to a 2D radiograph) that permits deformable motion between structures defined in the 3D image based on a series of locally rigid transformations. This invention utilizes predefined annotations in 3D images (e.g., the location of anatomical features of interest) to perform multiple locally rigid registrations that yield improved accuracy in aligning structures that have undergone deformation between the acquisition of the 3D and 2D images (e.g., a preoperative CT compared to an intraoperative radiograph). The 3D image is divided into subregions that are masked according to the annotations, and the registration is computed simultaneously for each divided region by incorporating a volumetric masking method within the 3D-2D registration process.

According to one embodiment, a medical image processing apparatus includes processing circuitry. The processing circuitry extracts a rigid region from predetermined medical image data among a plurality of items of medical image data. Further, between first medical image data and second medical image data among the plurality of items of medical image data, the processing circuitry performs rigid registration on the rigid region and performs non-rigid registration on a region other than the rigid region.

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.

The present invention relates to the technical field of medical image processing and, in particular, to a liver boundary identification method and a system. The method includes: obtaining liver tissue information of a liver tissue to be identified; identifying a liver tissue boundary in the liver tissue information according to a feature of the liver tissue corresponding to the liver tissue information and a feature of the liver tissue boundary corresponding to the liver tissue information using an image processing technology or a signal processing technology; and outputting position information of the identified liver tissue boundary. By using the disclosed method, the liver tissue boundary can be identified automatically, the efficiency of identifying the liver boundary can be improved, and automatic positioning of the liver boundary can thus be achieved.

A spinal alignment estimating apparatus 1 includes a memory, and a processor coupled to the memory, the processor being configured to obtain a position of a head of a user measured in relation to a viewing target, and an angle of the head of the user, and estimate a spinal alignment of the user based on the position and the angle.

Systems and methods for planning the position of surgical hardware to be robotically implanted in a subject. The system extracts information about the planned position of hardware from an operative plan based on preoperative images, and converts this information into mathematical vectors. Intraoperatively, at least one three-dimensional scan of the operative site is obtained. The intraoperative images are processed by image analysis, to which are applied artificial intelligence algorithms for feature identification. The vectors derived from the preoperative plan are superimposed on identified anatomical features from the processed intraoperative images. The surgical plan can then be updated intraoperatively, taking into account any shift in position of the anatomical features between the preoperative images and the intraoperative images, prior to robotic insertion of the hardware.