Abstract: CAD modeling method, system, and apparatus provide an on-demand mate controller for controlling settings of mating relationships in a CAD model. The names of mates of a CAD model assembly are auto-populated into an ordered list in the mate controller. The mate controller enables user interactive re-ordering of the listed names. With the mate controller, a user may temporarily unlock a mate, visually position assembly components, and relock the mate resulting in refined mate settings and degrees of freedom of assembly components. The mate controller enables a user to interactively change order of positions of the model assembly which in turn affects order of position changes in motion studies of the model assembly. The mate controller saves per position data of the model assembly including mate values and component degrees of freedom. The saved per position data can be readily used to create animations.

Abstract: Radiation-free simulator systems and methods for simulating fluoroscopic procedures or other medical procedures are provided. Simulator systems, methods and computer readable media are provided, comprising a physical, anatomical model of an anatomy of interest, at least one or more video camera positioned proximate the anatomical model and configured to transmit a live video feed or image of the anatomical model, a computer configured for combining a recorded video feed or 2D rendering of a 3D dataset of an actual anatomical area of interest with the live video feed or image of the anatomical model to form a composite image or video, and a display configured to display the composite image or video. A simulated fluoroscopic procedure can be performed on the anatomical model without radiation, and the simulated fluoroscopic procedure is viewable on the display.

Abstract: A method enhances a low quality video. An input video Vjin is acquired of a scene under uncontrolled illumination. The input video Vjin is smoothed to produce a noise-reduced video Sj. Temporal gradients Gtj (x, y) are determined for each frame j of the noise reduced video Sj. The gradients Gtj (x, y) are thresholded to generate a binary mask Mj(x, y). For each frame, weights are determined according Wj (x, y)=F(Mk(x, y), and a spatial gradient field is determined according to Gxyj (x, y). Then, an output video Vjout is constructed from the spatial gradient field Gxyj.

Abstract: A method generates an image with de-emphasized textures. Each pixel in the image is classified as either a silhouette edge pixel, a texture edge pixels, or a featureless pixel. A mask image M(x, y) is generated, wherein an intensity of a given pixel (x, y) in the mask image M(x, y) is zero if the pixel (x, y) is classified as the texture edge pixel, is d(x, y) if the pixel (x, y) is classified as the featureless pixel, and is one if the pixel (x, y) is classified as the silhouette edge pixel. An intensity gradient ?I(x, y) is determined in the masked image, and the intensity gradients in the masked image are integrated according to G(x, y)=?I(x, y). M(x, y). Then, an output image I? is generated by minimizing |?I??G|, and normalizing the intensities in the output image I?.

Abstract: A method enhances images of a naturally illuminated scene. First, a set of images Ii(x, y) is acquired of a scene. Each image is acquired under a different uncontrolled illumination. For each image Ii(x, y), intensity gradients ?Ii(x, y) are determined, and each image is weighted with weights according to the intensity gradients. The weighted images are then combined to construct an enhanced image I?.

Abstract: A method generates an image with de-emphasized textures. Each pixel in the image is classified as either a silhouette edge pixel, a texture edge pixels, or a featureless pixel. A mask image M(x, y) is generated, wherein an intensity of a given pixel (x, y) in the mask image M(x, y) is zero if the pixel (x, y) is classified as the texture edge pixel, is d(x, y) if the pixel (x, y) is classified as the featureless pixel, and is one if the pixel (x, y) is classified as the silhouette edge pixel. An intensity gradient ∇I(x, y) is determined in the masked image, and the intensity gradients in the masked image are integrated according to G(x, y)=∇I(x, y). M(x, y). Then, an output image I′ is generated by minimizing |∇I′−G|, and normalizing the intensities in the output image I′.

Abstract: A method enhances images of a naturally illuminated scene. First, a set of images Ii(x, y) is acquired of a scene. Each image is acquired under a different uncontrolled illumination. For each image Ii(x, y), intensity gradients ∇Ii(x, y) are determined, and each image is weighted with weights according to the intensity gradients. The weighted images are then combined to construct an enhanced image I′.