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 certain embodiments, the systems, apparatus, and methods disclosed herein relate to robotic surgical systems with built-in navigation capability for patient position tracking and surgical instrument guidance during a surgical procedure, without the need for a separate navigation system. Robotic based navigation of surgical instruments during surgical procedures allows for easy registration and operative volume identification and tracking. The systems, apparatus, and methods herein allow re-registration, model updates, and operative volumes to be performed intra-operatively with minimal disruption to the surgical workflow. In certain embodiments, navigational assistance can be provided to a surgeon by displaying a surgical instrument's position relative to a patient's anatomy. Additionally, by revising pre-operatively defined data such as operative volumes, patient-robot orientation relationships, and anatomical models of the patient, a higher degree of precision and lower risk of complications and serious medical error can be achieved.

Systems and methods for designing and implementing patient-specific surgical procedures and/or medical devices are disclosed. In some embodiments, a method includes receiving a patient data set of a patient. The patient data set is compared to a plurality of reference patient data sets, wherein each of the plurality of reference patient data sets is associated with a corresponding reference patient. A subset of the plurality of reference patient data sets is selected based, at least partly, on similarity to the patient data set and treatment outcome of the corresponding reference patient. Based on the selected subset, at least one surgical procedure or medical device design for treating the patient is generated.

A method for autonomous segmentation of three-dimensional nervous system structures from raw medical images, the method including: receiving a 3D scan volume with a set of medical scan images of a region of the anatomy; autonomously processing the set of medical scan images to perform segmentation of a bony structure of the anatomy to obtain bony structure segmentation data; autonomously processing a subsection of the 3D scan volume as a 3D region of interest by combining the raw medical scan images and the bony structure segmentation data, wherein the 3D ROI contains a subvolume of the bony structure with a portion of surrounding tissues, including the nervous system structure; autonomously processing the ROI to determine the 3D shape, location, and size of the nervous system structures by means of a pre-trained convolutional neural network (CNN).

An image processing apparatus obtains segment definition information that defines a plurality of segments obtained by dividing a human body along a body axis, and obtains a three-dimensional image including a plurality of slice images indicating cross sections of a subject. The image processing apparatus identifies, based on the segment definition information, a segment to which a cross section corresponding to at least one slice image among the slice images included in the image belongs, and calculates a coordinate value of the at least one slice image, based on the identified segment and a reference coordinate system in which a coordinate value is defined for each of the segments.

Surgical navigation system: 3D display system with see-through visor; a tracking system for real-time tracking of: surgeon's head, see-through visor, patient anatomy and surgical instrument to provide current position and orientation data; a source of an operative plan, a patient anatomy data and a virtual surgical instrument model; a surgical navigation image generator to generate a surgical navigation image with a three-dimensional image representing simultaneously a virtual image of the surgical instrument corresponding to the current position and orientation of the surgical instrument and a virtual image of the surgical instrument, the see-through visor, the patient anatomy and the surgical instrument; the 3D display system configured to show the surgical navigation image at the see-through visor, such that an augmented reality image collocated with the patient anatomy in the surgical field underneath the see-through visor is visible to a viewer looking from above the see-through visor towards the surgical field.

Various methods and systems are provided for scanning an image subject along a scan axis. The method includes stitching sectional datasets acquired from different anatomical sections of the image subject based on locations of a landmark in the sectional datasets.

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 Si 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 imaging method. The method comprises the following steps: determining a target by identifying target-related position information or characteristic information (S101); implementing a two-dimensional scan of the target to collect image data of the target in a three-dimensional space (S102); processing, during the scanning, and on a real-time basis, the image data and relevant spatial information to obtain a plurality of image contents of the target, and displaying the image content on a real-time basis (S103); and arranging the plurality of image contents in an incremental sequence to form an image of the target (S104). The imaging method prevents collection of unusable image information, shortens image data collection time, and increases the speed of an imaging process. The application further provides an imaging device.

The present application relates to a computer implemented method of identifying a channel between at least two objects from image data comprising a plurality of pixels or voxels. The method comprises a cycle comprising the steps of choosing a portion of the image data which contains image data of at least a part of at least two of the objects, calculating image gradients of the pixels or voxels of the portion of the image data, and analyzing an orientation of the image gradients. If at least two of the image gradients point into opposing directions, the chosen portion of the image data is determined to contain edges of the objects defining the channel. This method can subsequently be used to separate or segment the objects or parts of the objects defining the channel.