A method, apparatus, and system for reliably identifying a specific part of a spine in an image of a human or animal body, includes the steps of determining one or more parts of the spine in the image, determining one or more discriminative parameters for each of the one or more parts of the spine in the image, the discriminative parameters relating to at least one anatomical property of each of the one or more parts of the spine, classifying the discriminative parameters of the one or more parts of the spine in the image, and identifying a specific part of the spine based on the classification of the discriminative parameters of the one or more parts of the spine in the image. An identified vertebra, in particular the T12 vertebra and/or its associated intervertebral discs, can be used advantageously as a starting point of powerful automatic spine labeling algorithms.

The present invention relates to a method and apparatus for measuring rotation parameters of a spine on medical images. The method comprises: selecting a reference image and a movement image from the medical images; determining a lower spine image and an upper spine image in the reference image, and determining a lower spine image and an upper spine image in the movement image; registering the lower spine image in the movement image with the lower spine image in the reference image; correcting the upper spine image in the movement image according to output parameters of registration of the lower spine images; superposing the upper spine image in the reference image with the corrected upper spine image in the movement image to obtain a superposed image; and calculating to obtain the rotation parameters according to a position difference between the upper spine image in the reference image and the upper spine image in the movement image on the superposed image.

The present invention provides a method for spine position detection, comprising: obtaining 2D geometrical configuration of a current vertebra body selected from a plurality of vertebra bodies visible in an image on a sagittal plane defined by a horizontal component of an initial point, a geometrical template being applied to the current vertebra body and the 2D geometrical configuration of the current vertebra body being adjusted by a predetermined correlation evaluation; searching adjacent edge points of next vertebra body corresponding to a number of edge points of the current vertebra body by identifying the gradient values along the direction substantially perpendicular to the edge of the current vertebra body based on the adjusted 2D geometrical configuration of the current vertebra body; calculating height of an intervertebral disc located between the current vertebra body and the next vertebra body based on an average of the distances between the edge points of the current vertebra body and the corresponding adjacent edge points of the next vertebra body; determining 2D geometrical configuration of the next vertebra body based on the height of the intervertebral disc and the adjusted 2D geometrical configuration of the current vertebra body. Then the transverse images of the intervertebral discs can be formed to serve for diagnosis.

An image display control apparatus includes: an image obtaining unit that obtains an image of a backbone region that includes at least a portion of the backbone of a subject; an emphasized display target region specifying unit that specifies an emphasized display target region within the backbone region based on the image; a bone metastasis region specifying unit that specifies an osteolytic metastasis region included in the backbone region; and a display control unit that causes images to be displayed by a display unit. The display control unit displays an osteolytic metastasis region that belongs within the emphasized display target region with a greater degree of emphasis than an osteolytic metastasis region outside the emphasized display target region.

In some examples, a method includes receiving a medical image of at least a portion of a spine in a patient. The method includes supplying the medical image to a neural network trained using training spine images and, for each training spine image, one or more spine measurement annotations. The method includes detecting, using the neural network, five or more vertebral landmarks for each of a plurality of vertebral bodies depicted in the medical image. The method includes outputting, for at least a first vertebral body, one or more deformity measurements based on the vertebral landmarks for the first vertebral body.

A bone density estimating method, comprising: acquiring, by an MR scanning device, a magnetic resonance, MR, sequence of a body portion, wherein the MR sequence comprises quantitative information of the body portion; generating, by a processing circuit, an MR image of the body portion based on the MR sequence, wherein each voxel of the MR image represents a volume of the body portion; identifying, by the processing circuit, a part of the MR image representing a bone portion of the body portion; for a voxel of the identified part of the MR image, estimating a bone density of a volume of the bone portion represented by the voxel, based on a quantitative value of the voxel. The quantitative information of the body portion comprises a proton density.

Provided is a method for determining a position of an imaged anatomical body part of a patient. The method includes acquiring patient image data describing a digital image of at least part of a reference device and the anatomical body part, acquiring reference device model data describing a model of at least one of at least one internal surface or at least one external surface of the reference device, determining, —based on the patient image data and the reference device model data, reference device image position data describing a relative position between the reference device and the anatomical body part, acquiring reference device tracking data describing a position of the reference device in the tracking reference system, and determining, based on the reference device image position data and the reference device tracking data, body part tracking data describing a position of the anatomical body part in the tracking reference system.

Disclosed are systems and methods for rapid generation of simulations of a patient's spinal morphology that enable pre-operative viewing of a patient's condition and to assist surgeons in determining the best corrective procedure and with any of the selection, augmentation or manufacture of spinal devices based on the patient specific simulated condition. The simulation is generated by morphing a generic spine model with a three-dimensional curve representation of the patient's particular spinal morphology derived from existing images of the patient's condition.

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.

The present disclosure provides a medical image analysis method and apparatus. The medical image analysis method according to an exemplary embodiment includes: receiving a frontal image of a spine; separating vertebral bodies from a vertebrae constituting the spine in the frontal image and extracting a contour of each of the vertebral bodies; deforming a 3D vertebral body model prepared in advance to match with the contour of each vertebral body; detecting an upper plane and a lower plane of each vertebral body in a matched 3D vertebral body model; determining an inclination of each vertebral body based on the upper plane and the lower plane of each vertebral body; and calculating a Cobb's angle based on the inclination of the vertebral body.