Abstract: A method for segmenting intravascular images includes acquiring a series of digitized images acquired from inside a vessel, each said image comprising a plurality of intensities corresponding to a 2-dimensional grid of pixels, providing a precomputed set of shapes for modeling contours of vessel wall boundaries, wherein a contour can be expressed as a sum of a mean shape and a inner product of shape modes and shape weights, initializing a boundary contour for one of said set of images, initializing said shape weights by projecting a contour into said shape modes, updating said shape weights from differential equations of said shape weights, and computing a contour by summing said mean shape and said inner product of shape modes and updated shape weights.

Abstract: A method and apparatus for automatically detecting stent struts in an image is disclosed whereby the inner boundary, or lumen, of an artery wall is first detected automatically and intensity profiles along rays in the image are determined. In one embodiment, detection of the lumen boundary may be accomplished, for example, by evolving a geometric shape, such as an ellipse, using a region-based algorithm technique, a geodesic boundary-based algorithm technique or a combination of the two techniques. Once the lumen boundary has been determined, in another embodiment, the stent struts are detected using a ray shooting algorithm whereby a ray is projected outward in the OCT image starting from the position in the image of the OCT sensor. The intensities of the pixels along the ray are used to detect the presence of a stent strut in the image.

Abstract: A method for registering two three-dimensional shapes is disclosed whereby the two shapes are represented as zero level set of signed distance functions and the energy between these two functions is minimized. In a first embodiment, two undetailed ear impression models are rigidly registered with each other. In another embodiment, a detailed ear impression is initially aligned with an undetailed ear impression model and, then, the detailed ear impression model is rigidly registered with the undetailed ear impression model as a function of the signed distance functions. In accordance with another embodiment, an undetailed ear impression model is non-rigidly registered with a template ear impression model as a function of the signed distance functions.

Abstract: Certain exemplary embodiments can comprise a method, which can comprise, automatically determining a target object from an image via an application of an iterative minimization algorithm to an energy function. Each iteration of the iterative minimization algorithm can comprise a comparison of a model with an estimated contour of the target object.

Abstract: A method for segmenting a digitized ultrasound image includes providing a digitized in-phase/quadrature ultrasound image comprising a plurality of intensities defined on an N-dimensional grid, decorrelating the ultrasound image wherein spatial correlations are substantially reduced in the intensity data, modeling the decorrelated image intensities with a statistical distribution, propagating, an active contour in the image where the contour segments the image, where the contour is propagated based on the statistical distributions of intensity data inside and outside the active contour.

Abstract: A method of tracking a guidewire in video imagery includes: obtaining a first video image including pixels associated with features of a guidewire; selecting a set of parameters to define an open curve on the first video image; determining a feature map of the first video image using phase congruency; and updating the parameters of the open curve using the feature map to align the open curve to the pixels associated with the features of the guidewire.

Abstract: A method of computing a continuous interpolation of a discrete set of three-dimensional (3D) balls, including generating an initial skin, wherein the initial skin is a surface comprised of splines and wherein the splines touch each ball along a circle that is tangent to the ball, solving a first differential equation to minimize the initial skin's surface area or solving a second differential equation to minimize a squared mean curvature of the initial skin's surface, wherein the result of solving the first or second differential equations is an updated skin; and repeating the steps of solving the first or second differential equations for the updated skin, and then, repeating the steps of solving the first or second differential equations for each subsequently updated skin until a desired skin is realized.

Abstract: A method and apparatus for rounding a sharp edge of a model of an object is disclosed whereby a ball is propagated in a desired direction along the edge to be smoothed. The position of the ball at each point in its propagation is noted and, as a result, a virtual tunnel through which the ball passed may be constructed. Points on the sides of the surface of the object in proximity to the sharp edge are then projected onto the virtual tunnel by connecting with a line each point in proximity to the sharp edge to the center of the tunnel. New projected points are created at each position on the surface of the tunnel where the lines intersect that surface. The original points along the sharp edge are then hidden or deleted and the points along the virtual tunnel are connected via well-known surface reconstruction methods. In this way, a sharp edge of a triangle mesh model are advantageously smoothed.

Abstract: An exemplary method of detecting a structure in a three-dimensional (3D) computed tomography (“CT”) knee image is provided. An intensity prior mask is created based on a two-dimensional (2D) slice of the CT image. A seed point in the 2D slice is received or estimated. The seed point is in a Hoffa's pad region. A geometric prior mask is created based on the seed point. The intensity prior mask and the geometric mask are combined to form a region mask. A level-set contour is segmented from the 2D slice. The step of segmenting is constrained by the region mask.

Abstract: A computer-implemented method for vertebrae segmentation includes providing an image of a plurality of vertebrae, and determining a seed in each of at least two adjacent vertebrae in the image. The method further includes mapping a unit square to the seeds in the image as corresponding shape constraints on a segmentation, evolving the shape constraints to determine the segmentation of the adjacent vertebrae, wherein evolutions of the shape constraints interact, and outputting a segmented image indicating a location of the vertebra.

Abstract: A method and system for detecting the second bend plane of an ear canal surface is disclosed. A region of interest of the ear canal is defined between the first bend plane and the ear canal tip. A set of curves is defined in the region of interest and a set of high curvature points is detected from the set of curves. The second bend plane is detected using the set of high curvature points.

Abstract: A method and system for suppressing bone structures based on a single x-ray image is disclosed. The bone structure suppressing method predicts a soft-tissue image without bone structures from an input x-ray image. A set of features is extracted for each pixel of the input x-ray image. A soft-tissue image is then generated from the input x-ray image using a trained regression function to determine an intensity value for the soft-tissue image corresponding to each pixel of the input x-ray image based on the set of features extracted for each pixel of the input x-ray image. The extracted features can be wavelet features and the regression function can be trained using Bayesian Committee Machine (BCM) to approximate Gaussian process regression (GPR).

Abstract: A method and system for segmenting tubular structures in 3D images is disclosed. User inputs identifying a first region on the image inside of a tubular structure and a second region of the image outside of the tubular structure are received. Based on this information, an ordered series of pearls are generated along the tubular structure. Pearls are spheres, each having a center location and a radius determined based on the center locations and radii of previous pearls and on local voxel intensities in the image. A continuous model of the tubular structure can be generated by interpolating the center locations and radii of the ordered series of pearls. The ordered series of pearls can be displayed and easily edited in response to user input, thus providing an efficient and flexible method for interactive segmentation of a potion of interest in a tubular structure.

Abstract: A method and system for side detection of an undetailed 3D ear impression is disclosed. In order to determine whether a received 3D undetailed ear impression is a left or right ear impression, a local coordinate system of the 3D undetailed ear is defined based on side independent features of the 3D undetailed ear impression. A skeleton (or center spline) of the 3D undetailed ear impression is detected, and it is determined whether the 3D undetailed ear impression is a left or right ear impression based on the skeleton and the local coordinate system.

Abstract: A method for lesion segmentation in 3-dimensional (3D) digital images, includes selecting a 2D region of interest (ROI) from a 3D image, the ROI containing a suspected lesion, extending borders of the ROI to 3D forming a volume of interest (VOI), where voxels on the borders of the VOI are initialized as background voxels and voxels in an interior of the VOI are initialized as foreground voxels, propagating a foreground and background voxel competition where for each voxel in the VOI, having each neighbor voxel in a neighborhood of the voxel attack the voxel, and, if the attack is successful, updating a label and strength of the voxel with that of the successful attacking voxel, and evolving a surface between the foreground and background voxels in 3D until an energy functional associated with the surface converges in value, where the surface segments the suspected lesion from the image.

Abstract: A method and system for segmenting tubular or stroke-like structures in 2D images is disclosed. Examples of such structures include, but are not limited to, blood vessels, bones, roads, rivers, electrical wirings, and brush-strokes. User inputs identifying a first region on the image inside of a tubular structure and a second region of the image outside of the tubular structure are received. Based on this information, an ordered series of pearls are generated along the tubular structure. Pearls are 2D disks, each having a center location and a radius determined based on local pixel intensities in the image. A continuous model of the tubular structure is generated by interpolating the center locations and radii of the ordered series of pearls.

Abstract: A system and method for graph cut image segmentation using a shape prior is provided. In this method, an initial shape is applied to a portion of an image to be segmented. A narrowband is formed around a border of the shape, and a minimized graph cut is calculated for a portion of the image within the narrowband. The shape is then adjusted using the shape prior to fit the minimized graph cut. This method can be iteratively performed so that the shape evolves to segment an object from an image. The shape prior can be a parametric shape, such as an ellipse, or a statistical shape eigenspace calculated based on one or more training shapes.

Abstract: A method for rigid registration of ear impression models, including: extracting a canal region from an undetailed ear impression model, the undetailed ear impression model representing an undetailed surface of an ear canal and outer ear geometry; extracting a canal region from a detailed ear impression model, the detailed ear impression model representing a detailed surface of the ear canal; generating an orientation histogram for the canal region of the undetailed ear impression model and an orientation histogram for the canal region of the detailed ear impression model; performing a rotational alignment between the orientation histograms; computing a translational shift between the canal regions after performing the rotational alignment; and performing a registration between the undetailed and detailed ear impression models after computing the translational shift.

Abstract: A method and system for image segmentation by evolving radial basis functions (RBFs) is disclosed. A set of RBFs define a contour on an image. The contour is the zero level set of an implicit function defined by the RBFs. The RBFs are weighted and parameterized by multiple parameters, such as center point, standard deviation, and orientation. The contour is iteratively deformed by updating the weight and each of the parameters of each of the RBFs based on each pixel of the contour, until the contour converges. The parameters and the weight of each RBF is updated using coupled set of differential equations derived based from a region-based or boundary-based image segmentation energy formulation. The final contour at a convergence defines boundaries of a target object or region in the image.

Abstract: A method and system for structure enhancement and noise reduction of medical images using adaptive filtering is disclosed. The method utilizes feature estimation methods to determine multiple feature values for each pixel in an input image. Each pixel is then filtered using a filter type selected based on the feature values for that pixel.