Disclosed embodiments determine, at an early stage, suitability of an intraoperative image for further intraoperative surgical analysis. The determination of suitability may be made using a first angle (such as a first obturator angle) based on at least three pelvic feature points in a preoperative image, a corresponding second angle (such as a corresponding second obturator angle) based on at least three corresponding pelvic feature points in an intraoperative image, and by comparing the first angle and the corresponding second angle to determine intraoperative image suitability. The first intra-operative image is indicated as suitable for further intraoperative analysis when an absolute value of a difference between the first angle and the corresponding second angle does not exceed a threshold. When the intraoperative image is determined as unsuitable for further intraoperative analysis, an indication of a movement direction for a fluoroscopy camera used to capture the intraoperative image is provided.

A method includes applying both a first dedicated functional-anatomical registration scheme to a first volume of interest to deform the first volume of interest and a second dedicated functional-anatomical registration scheme to a second volume of interest to deform the second volume of interest, wherein the first volume of interest at least partially encompasses the second volume of interest. The method includes identifying or segmenting relevant organs or anatomical structures related to a first group and a second group in the first volume of interest and the second volume of interest, respectively; generating a spatially smooth-transition weight mask that gives higher weight to image data corresponding to the identified or segmented relevant organs or anatomical structures related to the first group and the second group; and generating a final cohesive registered image volume from the first image volume and the second image volume utilizing the spatially smooth-transition weight mask.

Presented are concepts for initialising a model for model-based segmentation of an image which use specific landmarks (e.g. detected using other techniques) to initialize the segmentation mesh. Using such an approach, embodiments need not be limited to predefined model transformations, but can initialise a segmentation mesh with arbitrary shape. In this way, embodiments may provide for an image segmentation algorithm that not only delivers a robust surface-based segmentation result but also does so for strongly varying target structure variations (in terms of shape).

A method of enhancing an x-ray image is disclosed. The method involves obtaining an input image based on a source x-ray image of an object. Compositional information representing physical characteristics of the object is also obtained. An image enhancement process is applied to the input image to generate a processed image. Application of the image enhancement process is controlled by one or more parameters determined in dependence on the compositional information. An output image is then provided based on the processed image.

An example method includes obtaining, a virtual model of a portion of an anatomy of a patient obtained from a virtual surgical plan for an orthopedic joint repair surgical procedure to attach a prosthetic to the anatomy; identifying, based on data obtained by one or more sensors, positions of one or more physical markers positioned relative to the anatomy of the patient; and registering, based on the identified positions, the virtual model of the portion of the anatomy with a corresponding observed portion of the anatomy.

A method for customizing an interactive control boundary includes positioning a virtual implant model relative to a virtual bone model based on a user input, and extracting reference feature information associated with the virtual implant model, wherein the reference feature information describes one of a point, a line, a plane, and a surface associated with the virtual implant model. The method further includes mapping the extracted reference feature information to the virtual model of the bone, and receiving information indicative of a positional landmark associated with the bone, then estimating an intersection between the positional landmark and the mapped reference feature and generating a virtual boundary based, at least in part, on the estimated intersection between the positional landmark and the mapped reference feature.

Embodiments of the present disclosure provide a software program that displays both a volume as images and segmentation results as surface models in 3D. Multiple 2D slices are extracted from the 3D volume. The 2D slices may be interactively rotated by the user to best follow an oblique structure. The 2D slices can “cut” the surface models from the segmentation so that only half of the models are displayed. The border curves resulting from the cuts are displayed in the 2D slices. The user may click a point on the surface model to designate a landmark point. The corresponding location of the point is highlighted in the 2D slices. A 2D slice can be reoriented such that the line lies in the slice. The user can then further evaluate or refine the landmark points based on both surface and image information.

Systems and methods are disclosed for use in electronic guidance systems for surgical navigation. A sensor is provided with an optical sensor, to provide optical information, and a measuring sensor, to provide measurements for determining a direction of gravity. The sensor communicates optical information and measurements to an inter-operative computing unit. In an embodiment, the inter-operative computing unit receives first optical information for a registration device and a patient anatomy and a measurement to determine a direction of gravity to perform a registration step. The inter-operative computing unit receives second optical information for the patient anatomy and an object and determines and presents measurements relative to the anatomy. The measurements relative to the anatomy are determined from the second optical information, and in relation to the registration of the anatomy of the patient.

A patient-specific assessment of fracture probability for the femur proximal end is provided. 3D locations of the femur head center, a point on the femoral shaft center, and the femoral intercondylar notch are determined from a clinical image. A frontal plane, a perpendicular thereunto and a bone shaft axis are determined from the 3D locations. An FEA coordinate system is defined from the frontal plane, the perpendicular and the axis. Two FEA analyses are performed, one for neck fracture and one for pertrochanteric fracture, with the same displacement constraints and the same load magnitude but different load angles. The femur proximal end is divided into four anatomically-based regions. For each region and each load, maximum tensile and compressive principal strains are determined and, based on the body weight and the principal strains, a likelihood of fracture is obtained. The minimum of these 8 likelihoods gives the probability of fracture.

Methods and systems disclosed herein relate generally to processing images to estimate whether at least part of a tumor is represented in the images. A computer-implemented method includes accessing an image of at least part of a biological structure of a particular subject, processing the image using a segmentation algorithm to extract a plurality of image objects depicted in the image, determining one or more structural characteristics associated with an image object of the plurality of image objects, processing the one or more structural characteristics using a trained machine-learning model to generate estimation data corresponding to an estimation of whether the image object corresponds to a lesion or tumor associated with the biological structure, and outputting the estimation data for the particular subject.