Abstract: Example methods, apparatus and articles of manufacture to adaptively reconstruct medical diagnostic images are disclosed. A disclosed example method includes storing non-reconstructed image data captured by a medical image acquisition system, receiving a parameter representing a region of interest from a diagnostic imaging workstation, and communicating a portion of the non-reconstructed image data associated with the region of interest to the diagnostic imaging workstation in response to receiving the parameter, wherein the portion of the non-reconstructed image data is processed by the diagnostic imaging workstation to form a medical diagnostic image.

Abstract: A method for compensating respiratory motion in coronary fluoroscopic images includes finding a set of transformation parameters of a parametric motion model that maximize an objective function that is a weighted normalized cross correlation function of a reference image acquired at a first time that is warped by the parametric motion model and a first incoming image acquired at a second time subsequent to the first time. The weights are calculated as a ratio of a covariance of the gradients of the reference image and the gradients of the first incoming image with respect to a root of a product of a variance of the gradients of the reference image and the variance of the gradients of the first incoming image. The parametric motion model transforms the reference image to match the first incoming image.

Abstract: There is provided an image processing apparatus that analyzes a pathology image obtained by imaging an analysis object including a setting device for calculating an amount of a luminance difference characteristic as an amount of characteristic of each pixel of a pathology image, and for setting a cellular tissue region in the pathology image, based on the amount of the luminance difference characteristic, using a cellular tissue detector that has studied in advance. The cellular tissue detector may have studied in advance by statistical learning that uses an image corresponding to a cellular tissue.

Abstract: A software implemented system and method for algorithmic correction of systematic image distortions within fingerprint imaging systems. The system and method may implement a three dimensional geometric model of a fingerprint imaging system to discover where a configuration prescribed by a conceptual fingerprint imaging system and an actual configuration of a manufactured fingerprint imaging system differ. By describing this difference using the geometric model, images captured by the manufactured fingerprint imaging system can be rectified in operational use to generate rectified images with relatively low amounts of distortion present.

Abstract: A method for fingerprinting a video involving identifying motion within the video and using a measure of the identified motion as a fingerprint. Once videos are fingerprinted, these fingerprints can be used in a method for identifying video. This involves creating a motion fingerprint for unidentified videos; comparing the fingerprints of the known and unknown videos, and identifying whether the unknown video is a copy of the known video based on the step of comparing.

Abstract: Some embodiments allow a video editor to remove unwanted camera motion from a sequence of video images (e.g., video frames). Some embodiments are implemented in a video editing application. Some of these embodiments distinguish unwanted camera motion from the intended underlying motion of a camera (e.g., panning and zooming) and/or motion of objects within the video sequence.

Abstract: A method for curved planar reformation of an image includes receiving a data volume including a medial axis tree of a vessel tree, determining a global rotation axis of the medial axis tree, and casting a line segment from a vessel tree root of the medial axis tree into a predefined direction perpendicular to the global rotation axis. The method includes projecting the medial axis tree onto a reference plane along the line segment. The method further includes re-sampling, from at least one medial axis point of a reference plane, the data volume using a vector perpendicular to a medial axis tangent of the reference plane, wherein the vector defines a sampling direction. The method includes rendering an image of the vessel tree along the vector.

Abstract: A computer-implemented method for combinational computer aided diagnosis (C-CAD) includes providing volume data of tissue, providing a database of disease and pathologies, and providing action items for processing the volume data. The method further comprises selecting at least two diseases of interest for the volume data, selecting at least one action item to be performed for each selected disease, determining a set of decision rules based on an output of a selected action item, and producing a combinational report predicting of the tissue of the volume data.

Abstract: A system and method track a face moving through multiple frames of a video sequence. A predicted position of a face in a video frame is obtained. A search is performed to determine appearance model similarity values of a detected face. Motion and appearance probabilities of the detected face are obtained, and the detected face in the video frame is associated with a track as a function of a joint probabilistic data association filter.

Abstract: The present invention relates to a method of identifying a target object in an image using image processing. It further relates to apparatus and computer software implementing the method. The method includes storing template data representing a template orientation field indicative of an orientation of each of a plurality of features of a template object; receiving image data representing the image; processing the image data to generate an image orientation field indicating an orientation corresponding to the plurality of image features; processing the image orientation field using the template orientation field to generate a match metric indicative of an extent of matching between at least part of the template orientation field and at least part of the image orientation field; and using the match metric to determine whether or not the target object has been identified in the image. Image and/or template confidence data is used to generate the match metric.

Abstract: The path and/or position of an object is tracked using two or more cameras which run asynchronously so there is need to provide a common timing signal to each camera. Captured images are analyzed to detect a position of the object in the image. Equations of motion for the object are then solved based on the detected positions and a transformation which relates the detected positions to a desired coordinate system in which the path is to be described. The position of an object can also be determined from a position which meets a distance metric relative to lines of position from three or more images. The images can be enhanced to depict the path and/or position of the object as a graphical element. Further, statistics such as maximum object speed and distance traveled can be obtained. Applications include tracking the position of a game object at a sports event.

Abstract: An object determining device includes imaging means for obtaining an image of the object, likelihood value calculating means for calculating a first likelihood value for the object shown in the image by use of the image obtained by the imaging means and a machine learning system and for calculating a second likelihood value for the object shown in the image by use of the image obtained by the imaging means and another machine learning system, the first likelihood value indicating a level of likelihood that the object is wearing the covering and the second likelihood value indicating a level of likelihood that the object is not wearing the covering, and determining means for determining whether or not the object, shown in the image obtained by the imaging means, is wearing a covering, on the basis of a ratio between the first likelihood value and the second likelihood value.

Abstract: An imaging system includes a two-dimensional detector having a plurality of cells wherein each cell is configured to detect energy or signal passing through an object. The imaging system includes a computer programmed to acquire imaging data for the plurality of cells, identify a cell to be corrected, based on the imaging data, interpolate Ix and Iy for the identified cell based on neighbor cells, and calculate local gradients gx and gy between the identified cell and its neighbor cells based on the interpolation. The computer is further programmed to calculate weighting factors wx and wy based on the local gradients, calculate a corrected final value I(0,0) for the identified cell, and correct the identified cell with the corrected final value.

Abstract: A target tracking apparatus and method according to an exemplary embodiment of the present invention may quickly and accurately perform target detection and tracking in a photographed image given as consecutive frames by acquiring at least one target candidate image most similar to a photographed image of a previous frame among prepared reference target images, determining one of the target candidate images as a target confirmation message based on the photographed image, and calculating a homography between the determined target confirmation image and the photographed image, and searching the photographed image of the previous image for feature points according to the calculated homography, and tracking an inter-frame change from the previous frame of the found feature points to a current frame.

Abstract: A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.

Abstract: A method and system comprising: generating at least one slice image by carpeting a multitude of digital images based upon a two-dimensional (2-D) reference system, each of the multitude of digital images associated with a location in the 2-D reference system and each showing a representation of an arborization and/or landmark such that digital images not showing a representation of an arborization and/or landmark are excluded; carpeting the multitude of digital images together to create a slice image; aligning the slice image with other similarly created slice images using landmark information to determine the amount of 2-D rotation and/or translation to be applied to each slice image; vectorizing the representation of the arborization on each slice image, the vectorization creating a series of segments; assigning a type to at least one of the series of segments based on a unique characteristic of arborization; and grouping related segments together.

Abstract: A technique for selecting portions of a medical image data set to be stored and portions of the medical image data set to be discarded in order to reduce the overall amount of image data that is stored for each image data set. The selection is based on the clinical purpose for obtaining the medical image data. The clinical purpose for obtaining the medical image is used to select an atlas. The atlas is labeled with information that establishes the relative relevance of various regions of the atlas. The atlas is aligned to the image and the labeling information is transferred from the atlas to the medical image. Each region of the medical image is then processed based on the labeling information received from the atlas. The regions of greatest relevance are stored at their full resolution. Regions of lesser relevance are stored at less than the full resolution. Finally, regions of no relevance are discarded and not stored at all.

Abstract: A method for fingerprinting a video involving identifying motion within the video and using a measure of the identified motion as a fingerprint. Once videos are fingerprinted, these fingerprints can be used in a method for identifying video. This involves creating a motion fingerprint for unidentified videos; comparing the fingerprints of the known and unknown videos, and identifying whether the unknown video is a copy of the known video based on the step of comparing.

Abstract: Systems and methods for detecting visual objects by employing multiple cues include statistically combining information from multiple sources into a saliency map, wherein the information may include color, texture and/or motion in an image where an object is to be detected or background determined. The statistically combined information is thresholded to make decisions with respect to foreground/background pixels.

Abstract: One embodiment of the present invention provides a system for applying a bilateral filter to an image. During operation, the system selects a first region within the image which is associated with a first pixel. Next, the system constructs a first histogram using pixel values within the first region. The system then computes a new value for the first pixel using the current value of the first pixel and the first histogram. The system then selects a second region within the image which is associated with a second pixel. Next, the system determines a non-overlapping region between the first region and the second region. The system then constructs a second histogram using the first histogram and pixel values in the non-overlapping region. Next, the system computes a new value for the second pixel using the current value of the second pixel and the second histogram.