Methods and systems for performing computer-assisted image-guided surgery, including robotically-assisted surgery. A method of displaying image data includes displaying image data of a patient on a handheld display device, tracking the handheld display device using a motion tracking system, and modifying the image data displayed in response to changes in the position and orientation of the handheld display device. Further embodiments include a sterile case for a handheld display device, display devices on a robotic arm, and methods and systems for performing image-guided surgery using multiple reference marker devices fixed to a patient.

In an approach to automatic detection of vertebral dislocations, training data is received, where the training data includes an ordered sequence of radiographic image patches of vertebrae and intervertebral spaces, and location data for each vertebra and each intervertebral space. Location deep learning models are trained to detect a location of each vertebra and each intervertebral space from the training data. Classification deep learning models are trained to classify an ordered sequence of image patches to identify vertebral anomalies of the vertebrae and the intervertebral spaces from the training data. Responsive to receiving radiographic image files, the location deep learning models and the classification deep learning models are applied to the radiographic image files to create a condition assessment.

A method and system for detecting spinal stenosis is provided. The method may receive image data corresponding to a spine region of a patient. The method may also identify a spinal cord in the image data. The method may determine at least one compression of the spinal cord and may mark an anatomical element proximate to a location of the determined at least one compression to yield at least one marking. The method may generate a decompression plan based on the at least one marking.

According to some embodiments, the process includes the steps of: a) taking a sagittal preoperative x-ray of the vertebral column of the patient to be treated, extending from the cervical vertebrae to the femoral heads; b) on that x-ray, identifying points on S1, S2, T12 et C7; c) depicting, on the said x-ray, curved segments beginning at the center of the plate of S1 et going to the center of the plate of C7; e) identifying, on that x-ray, the correction(s) to be made to the vertebral column, including the identification of posterior osteotomies to make; f) pivoting portions of said x-ray relative to other portions of that x-ray, according to osteotomies to be made; g) performing, on said x-ray, a displacement of the sagittal curvature segment extending over the vertebral segment to be corrected; h) from a straight vertebral rod (TV), producing the curvature of that rod according to the shape of said sagittal curvature segment in said displacement position.

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.

Image processing and analysis technique includes using a computer apparatus to assess a patient's magnetic resonance images or derived multiparametric maps for pathology and then automatically generate a prescription based at least in part on that assessment. The parametric maps are derived from a CT or Mill sequence from which multiparametric maps are derivable.

The present disclosure directs to a system and method for image processing. The method for image processing comprises acquiring a plurality of original computed tomography (CT) images of a spine of a subject; generating CT value images of the spine of the subject by processing the plurality of original CT images. The method further includes identifying an optimal sagittal image in which a centerline of the spine is located based on the CT value images. The method further includes identifying the centerline of the spine within the optimal sagittal image. The method further includes identifying a center point and a direction of at least one intervertebral disc along the centerline of the spine. The method still further includes reconstructing an image of the at least one intervertebral disc based on the center point and the direction of the at least one intervertebral disc.

A method of generating a quantitative characterization of injury presence and status of spinal cord tissue using an adaptive CNN system for use in diagnostic assessment, surgical planning, and therapeutic strategy comprises preprocessing for artifact correction of diffusion based, spinal cord MRI data, training an adaptive CNN system with healthy and abnormal (injured/pathologic) spinal cord images obtained by imaging a population of healthy, typically developed spinal cord subjects and subjects with spinal cord injury, evaluating a novel, diffusion-based MRI image for injury biomarkers using the adaptive CNN system, generating a three-dimensional predictive axonal damage map for quantitative characterization and visualization of the novel, diffusion-based MRI image, and transmitting the sets of healthy and injured spinal cord images back to a central database for continued improvement of the adaptive CNN system training. A system for defining a predictive spinal axonal damage map is also described.

A system for surgical planning and assessment of spinal deformity correction is provided that has a spinal imaging system and a control unit. The spinal imaging system is configured to collect at least one digitized position of one or more vertebral bodies of a subject. The control unit is configured to receive the at least one digitized position, and calculate, based on the at least one digitized position, an optimized posture for the subject. The control unit is configured to receive one or more simulated spinal correction inputs, and based on the inputs and optimized posture, predict an optimal simulated postoperative surgical correction.

A method and system for image processing is provided. The technique incudes acquiring data related to the processing, performing a pre-processing of the data, performing a segmentation of a subject, performing a post-processing of the result of the segmentation and managing storage of the data. The post-process incudes a calibrating and a rendering of the data.