The present disclosure relates to an image processing method. The method may include: obtaining image data; reconstructing an image based on the image data, the image including one or more first edges; obtaining a model, the model including one or more second edges corresponding to the one or more first edges; matching the model and the image; and adjusting the one or more second edges of the model based on the one or more first edges.

An image processing apparatus includes an image acquisition unit that acquires a first image and a second image acquired by capturing images of a subject including a plurality of bone parts at different times, a converted image acquisition unit that performs super-resolution processing for at least one of the first image or the second image to acquire at least one of a first converted image or a second converted image, a registration processing unit that performs a registration process for the plurality of bone parts in at least one of a combination of the first converted image and the second image, a combination of the first image and the second converted image, or a combination of the first converted image and the second converted image, and a difference image acquisition unit that applies a result of the registration process to the first image and the second image to acquire a difference image between the first image and the second image.

Systems, methods and circuits can perform automated pedicle placement planning on 3D image data sets of the spine using global and local coordinate axes systems and ray casting to identify a center of the vertebral foramen and a center of a solid vertebral body for the local coordinate axis system.

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 for determining an acceptable spinal surgical plan for a subject using pathology prediction, comprising generating a potential spinal surgical plan, obtaining clinically relevant data of the subject, obtaining pre-operative three-dimensional images of a spinal region of the subject, determining relationships between pairs of vertebrae in the images, predicting relationships between pairs of vertebrae that are expected from the surgical plan, accessing a multiple patient database, obtaining sets of data from the database for patients with similar characteristics to the subject, determining risks of pathology types for the subject, using artificial intelligence to combine the determined risks to calculate an overall risk for pathology types for the subject, and if the overall risks are unacceptable, selecting an alternative spinal surgical plan, and if the said overall risks are acceptable, determining that said surgical plan is acceptable.

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.

A method of modeling lungs of a patient includes acquiring computed tomography data of a patient's lungs, storing a software application within a memory associated with a computer, the computer having a processor configured to execute the software application, executing the software application to differentiate tissue located within the patient's lung using the acquired CT data, generate a 3-D model of the patient's lungs based on the acquired CT data and the differentiated tissue, apply a material property to each tissue of the differentiated tissue within the generated 3-D model, generate a mesh of the 3-D model of the patient's lungs, calculate a displacement of the patient's lungs in a collapsed state based on the material property applied to the differentiated tissue and the generated mesh of the generated 3-D model, and display a collapsed lung model of the patient's lungs based on the calculated displacement of the patient's lungs.

An exemplary method of determining a surgical spinal correction for a subject using analysis of motion capture images of the subject, which uses the steps of obtaining pre-operative three-dimensional images of a spinal region, obtaining a pre-operative time sequenced set of images of the subject during a movement progression of said subject, calculating in a plurality of the motion capture images, alignment parameters relating to upper and lower body regions of the subject, and determining if any of the calculated alignment parameters are outside their predetermined acceptable ranges in one or more of the images, iteratively adjusting anatomical elements in three-dimensional images until all of the calculated alignment parameters are within their predetermined acceptable ranges; and adjusting spinal anatomy in the three-dimensional images according to the degree of adjustment of spinal parameters in the motion capture images to determine a surgical spinal correction.

Disclosed herein are a method and a system for creating a registered image that integrates the information of CT and CBCT images. With the present method and system, medical practitioners can precisely transform the information of CT image-based treatment plan into the CBCT image so as to accurately control the dosage and location of a radiation therapy. Accordingly, also disclosed herein are methods of treating a cancer in the subject with the aid of the method and/or system of the present disclosure.

A method of matching medical images according to user-defined matches rules. In one embodiment, the matched medical images are displayed according user-defined display rules such that the matched medical images may be visually compared in manner that is suitable to the viewer's viewing preferences.