A system for visualizing a surgical site is provided. The system includes a robotic mechanism for performing a procedure on a patient, an imaging device coupled to the robotic mechanism, the imaging device configured to provide image data of a site of interest, and a computing device coupled to the imaging device. The computing device includes one or more processors and at least one memory device configured to store executable instructions. The executable instructions, when executed by the processor, are configured to receive the image data of the site of interest, track motion patterns of the site of interest in the received image data, filter the received image data to remove line-of-sight restrictions therein and alter pixels therein based on the tracked motion patterns, and generate an output frame from the filtered image data. The system also includes a presentation interface device coupled to the computing device and configured to present the output frame for visualization of the site of interest.

Systems and methods are provided for use in image-guided surgical procedures, in which intraoperatively acquired surface data is employed to verify the correspondence between intraoperatively selected fiducial points and volumetric fiducial points, where the volumetric fiducial points are selected based on volumetric image data. Segmented surface data obtained from the volumetric image data is registered to the intraoperative surface data using the intraoperative and volumetric fiducial points for initial surface alignment, and this process is repeated for other permutations of the correspondence between the intraoperatively fiducial points and the volumetric fiducial points. Quality measures may be determined that relate to the registration quality for each fiducial correspondence permutation, where the quality measures may be employed to assess of the likelihood that the initially prescribed fiducial correspondence is correct. A graphical representation may be generated for visually displaying the alignment of the registered surfaces for the different fiducial correspondence permutations.

Some embodiments of the present disclosure provide a pneumothorax detection method performed by a computing device. The method may comprise obtaining predicted pneumothorax information, predicted tube information, and a predicted spinal baseline with respect to an input image from a trained pneumothorax prediction model; determining at least one pneumothorax representative position for the predicted pneumothorax information and at least one tube representative position for the predicted tube information, in a prediction image in which the predicted pneumothorax information and the predicted tube information are displayed; dividing the prediction image into a first region and a second region by the predicted spinal baseline; and determining a region in which the at least one pneumothorax representative position and the at least one tube representative position exist among the first region and the second region.

The technology relates to generating a three-dimensional point cloud model of an anatomical structure. A computer accessible memory stores a three-dimensional array of data elements describing multiple anatomical features of a subject, each of the data elements having associated therewith positional data and a separate parameter value. A processor may be configured to identify any data elements in the three-dimensional array having an associated parameter value satisfying a predefined threshold value associated with at least one anatomical feature. The processor may be further configured to generate a visually displayable three-dimensional point cloud model of at least one anatomical structure having a first plurality of points in the point cloud model which define an exterior perimeter of the at least one anatomical structure and a second plurality points in the point cloud model which define at least one feature interior of the exterior perimeter of the at least one anatomical structure.

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.

An image processing system and method is provided. The image processing system includes a display, a processor, and a memory. The memory stores processor-executable code that when executed by the processor causes receiving an image of a region of interest of a patient with a medical catheter, tube or line disposed within the region of interest, detecting the medical tube or line within the image, generating a patient coordinate system relative to an anatomy of the patient within the image, generating a combined image by superimposing a first graphical marker on the image that indicates an end of the medical catheter, tube or line, and a second graphical marker on the image that indicates patient coordinate system, and displaying the combined image on the display. In addition, the system assesses common visualizable complications associated with CVC placement, including but not limited to hydrothorax, pneumothorax, pneumomediastinum and CVC position changes between x-rays taken at different times.

The present disclosure provides an apparatus of identifying a vertebral body from a medical image, and the apparatus includes a vertebral bone identification module configured to identify the vertebral body based on a multi-slice medical image provided from an outside, in which the vertebral identification module reconstructs the multi-slice medical image to create a three-dimensional medical image, obtains a coronal projection image for the three-dimensional medical image by projecting the three-dimensional medical image in a coronal plane direction, divides the coronal projection image into a selection area including at least one of a lumbar and a thoracic, obtains area information corresponding to the selection area in the three-dimensional medical image based on the divided selection area, and performs numbering on the vertebral body based on the area information and the three-dimensional medical image.

A system and techniques for creating a spine stress map are provided. The system may be configured to generate a multi-class segmentation for an anatomical element of a patient based on a plurality of magnetic resonance images of the anatomical element from a plurality of patients. Additionally, one or more stress maps may be generated based on simulating stresses on the anatomical element. In some embodiments, the simulated stresses may be simulated using a finite element analysis based at least in part on the multi-class segmentation. Additionally, the system may be configured to display one or more stress maps via a user interface, where the one or more stress maps are determined based on one or more deep learning models configured to predict multi-labeled masks and/or stress maps for the anatomical element.

A separation unit that generates a separated image in which a plurality of structures are separated, from an image including the plurality of structures receives an input of an image pair that includes a target image relating to at least a part of the plurality of structures and a non-separation image not including the structure, to output a separation image in which one of the structures is extracted from the target image. The separation unit receives an input of a new image pair including the target image and the separation image, to output a new separation image in which another one of the structures is extracted from the target image. The separation unit repeats the reception of the input of the new image pair including the target image and the new separation image and the output of a new separation image in which another one of the structures is extracted from the target image.

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.