Abstract: Among other things, one or more systems and/or techniques for segmenting a representation of a sheet object from an image are provided herein. To identify elements of an image (e.g., pixels and/or voxels) representative of sheet objects, a constant false alarm rate (CFAR) score and a topological score are computed for respective elements being analyzed. The CFAR score indicates a relationship between an element and a neighborhood of elements when viewed as a collective unit. The topological score indicates a relationship between the element and a neighborhood of elements when viewed neighbor-by-neighbor. When the CFAR score is within a specified range of CFAR scores and the topological score is within a specified range of topological scores, the element is labeled as being associated with a sheet object. A connected component labeling (CCL) approach may be used to group elements labeled as being associated with a sheet object.

Abstract: A method for extending initial image data of a subject for dose estimation includes obtaining first image data of the subject for dose calculation, wherein the first image data has a first field of view. The method further includes obtaining second image data for extending the field of view of the first image data. The second image data has a second field of view that is larger than the first field of view. The method further includes extending the first field of view based on the second image data, producing extended image data.

Abstract: In a method and apparatus for providing a visualization image and a reference image for a patient, with only one reconstruction being implemented, raw scan data from the patient are reconstructed into a visualization image, and the reference image is generated, without another reconstruction, by applying a filter to the visualization image to obtain a simulated reference image, using a value of a filter parameter that is specific for the patient. The patient-specific filter parameter is determined by comparing image-derived properties of an accessed, previously-reconstructed reference image and the reference image, and the filter parameter is adapted to reduce differences in the image-derived properties of the respective images.

Abstract: A system and method are disclosed for determining the presence and period of dashed line lane markers in a roadway. The system includes an imager configured to capture a plurality of high dynamic range images exterior of the vehicle and a processor, in communication with the at least one imager such that the processor is configured to process at least one high dynamic range image. The period of the dashed lane markers in the image is calculated for detecting the presence of the dashed lane marker and for tracking the vehicle within the markers. The processor communicates an output for use by the vehicle for use in lane departure warning (LDW) and/or other driver assist features.

Abstract: A method includes receiving first data defining a first bounding box for a first image of a sequence of images. The first bounding box corresponds to a region of interest including a tracked object. The method also includes receiving object tracking data for a second image of the sequence of images, the object tracking data defining a second bounding box. The second bounding box corresponds to the region of interest including the tracked object in the second image. The method further includes determining a similarity metric for first pixels within the first bounding box and search pixels within each of multiple search bounding boxes. Search coordinates of each of the search bounding boxes correspond to second coordinates of the second bounding box shifted in one or more directions. The method also includes determining a modified second bounding box based on the similarity metric.

Abstract: A digital image and a text string is received. The text string can be processed to identify at least a time frame and determine whether the time frame is a future time frame or a past time frame. How at least one element of the first digital image will change or has changed during the time frame can be predicted. At least one reference digital image can be generated, the reference digital image including at least one change to the at least one element corresponding to how the at least one element will change or has changed during the time frame. The reference digital image to each of a plurality of other digital images. A correlation parameter can be assigned to each of the plurality of other digital images. A portion of the plurality of other digital images having highest correlation parameters can be output for presentation to a user.

Abstract: A method may include determining a value indicative of an average intensity of blocks in an image. The blocks include a primary and outer blocks. Each of the outer blocks may have three, five, or more than five pixels. The image may describe an external pixel lying between the primary and at least one of the outer blocks. The external pixel may not contribute to the value indicative of the average intensity of any of the blocks. The image may also describe a common internal pixel lying within two of the blocks. The common pixel may contribute to the value indicative of the average intensity of the two of the blocks. The method may include comparing the value indicative of the average intensity of the primary block to the values of the outer blocks, and quantifying a feature represented by the image by generating a characteristic number.

Abstract: An image processing system includes a first processor that acquires frames of image data. For each frame of data, the first processor generates a Gaussian pyramid for the frame of data, extract histogram of oriented gradient (HOG) descriptors for each level of the Gaussian pyramid, compresses the HOG descriptors, and sends the compressed HOG descriptors. A second processor is coupled to the first processor and is configured to receive the compressed HOG descriptors, aggregate the compressed HOG descriptors into windows, compare data of each window to at least one stored model, and generate output based upon the comparison.

Abstract: A discriminator generation device 10 includes a feature quantity extraction unit 13 which, using at least two pattern groups having patterns of different sizes for a detection object, extracts a feature quantity of patterns configuring each pattern group, and a discriminator generation unit 14 which generates a discriminator for detecting a detection object of a size corresponding to each pattern group in an image based on the feature quantity of the patterns of each pattern group.

Abstract: The disclosed technology relates generally to medical imaging, and more particularly, some embodiments relate to systems and methods for creating and using a covariate modulated or “dynamic” atlas. Some embodiments of the disclosure provide a method for predicting an alas using General Additive Model (GAM) parameters, wherein the GAM parameters are derived by registering (and optionally segmenting) a plurality of image data sets from a plurality of different subjects to an initial atlas estimate (e.g., a seed atlas), and analyzing the resulting registration, segmentation, and intensity parameters as correlated with input covariates.

Abstract: The present invention relates to a method for classification of an organ in a tomographic image. The method comprises the steps of receiving (102) a 3-dimensional anatomical tomographic target image comprising a water image data set and a fat image data set, each with a plurality of volume elements, providing (104) a prototype image comprising a 3-dimensional image data set with a plurality of volume elements, wherein a sub-set of the volume elements are given an organ label, transforming (106) the prototype image by applying a deformation field onto the volume elements of the prototype image such that each labeled volume element for a current organ is determined to be equivalent to a location for a volume element in a corresponding organ in the target image, and transferring (108) the labels of the labeled volume elements of the prototype image to corresponding volume elements of the target image.

Abstract: A radiographic imaging control method includes combining a plurality of images by applying a first weight to the plurality of images, displaying a composite image, acquired by combining the plurality of images, newly receiving a second weight with respect to the composite image, recombining the plurality of images based on the received second weight, and displaying a recombined image, acquired by recombining the plurality of images.

Abstract: The present invention is directed to new methods of determining elongation, tension and applied pressure of elastic bandages comprising tension indicators. In one embodiment, a computer-implemented method of detecting elongation of an elastic bandage (e.g. on a mobile computing device having a processor and graphical user interface) is described. The method comprises receiving image data that includes a digital photograph of an elongated tension indicator of an elastic bandage; analyzing the image data to determine elongation of the elastic bandage by comparing geometric features of the elongated tension indicator to model geometric features that define a predetermined elongation state (such as an unelongated state); and providing output indicia associated with the determined elongation. Also described are various articles, some of which are intermediate articles of the methods described herein.

Abstract: An apparatus for performing a non-local means (NLM) filter is described. The pixel of the NLM-filtered image are weighted averages of pixels from a noisy image, where the weights are a measure of the similarity between patches of the noisy image. The similarity weights can be calculated using a Kullback-Leibler or a Euclidean distance measure. The similarity weights can be based on filtered patches of the noisy image. The similarity weights can be based on a similarity measure between patches of an anatomical image corresponding to the noisy image. The similarity weights can be calculated using a time series of noisy images to increase the statistical sample size of the patches. The similarity weights can be calculated using a weighted sum of channel similarity weights calculated between patches of noisy image that have been band-pass filtered. The NLM-filtered image can also be blended with a non-NLM-filtered image.

Abstract: Processing of images acquired via fluorescence microscopy by identifying broadband and other undesired signals from the component signals of a scanned image, and processing selected regions of the image that are known to contain signals of interest, thereby extracting or identifying desired signals while subtracting undesired signals. One or more broadband signals are recognized by their unique signature and ubiquitous dispersion through the image. Regions of the scanned image may be tagged as consisting of predominantly broadband signals and are ignored during a spectral unmixing process. The remaining regions of the image, or selected regions of the image known to contain desired signals, may be unmixed, and the plurality of reference spectra subtracted from the components to extract or identify the target signals. The set of target signals may be refined by eliminating known or obvious sources of noise by, for instance, being compared to known or ideal sets of signals from similar materials.

Abstract: A method for optimizing the position and size of a search window in a tracking system is disclosed. According to some embodiments of the present invention, the method may comprise: calculating a velocity of a tracked object based on comparison of at least two previously captured consecutive frames; calculating an expected position of the tracked object in a subsequent frame based on calculated velocity of the tracked object; determine possible positions of the tracked object in the subsequent frame, based on the last known position of the tracked object, status of the tracked object, the expected position and the acceleration of the tracked object; and optimizing the size and position of the search window within the subsequent frame so that the search window covers the expected position and at least one of the possible positions of said tracked object.

Abstract: The disclosure provides an approach for estimating depth in a scene. According to one aspect, regions where the depth estimation is expected to perform well may first be identified in full-resolution epipolar-plane images (EPIs) generated from a plurality of images of the scene. Depth estimates for EPI-pixels with high edge confidence are determined by testing a number of discrete depth hypotheses and picking depths that lead to highest color density of sampled EPI-pixels. The depth estimate may also be propagated throughout the EPIs. This process of depth estimation and propagation may be iterated until all EPI-pixels with high edge confidence have been processed, and all EPIs may also be processed in this manner. The EPIs are then iteratively downsampled to coarser resolutions, at which edge confidence for EPI-pixels not yet processed are determined, depth estimates of EPI-pixels with high edge confidence made, and depth estimates propagated throughout the EPIs.

Abstract: Techniques are described for vehicle or entity tracking. In one example, techniques include receiving a first set of data, said data comprising video or images from a first mobile data source, determining that said first set of data matches a second set of data in a first data source, the second set of data corresponding to a vehicle or entity being tracked; requesting a third set of data, said data comprising video or images from a second mobile data source, and determining a confidence level based on how well said first and third data sets match said second data set.

Abstract: Disclosed are a method for processing a magnetic resonance (MR) image of a dynamic object and an MRI apparatus. The method includes receiving, from the dynamic object, a plurality of MR signals that correspond to a plurality of time sections and a plurality of slices, generating a plurality of MR images by using the plurality of MR signals, performing segmentation of each of the plurality of MR images into a plurality of regions, determining whether a segmentation error occurs in each of the plurality of MR images, and arranging the plurality of MR images to correspond to the respective time sections and the respective slices to display a matrix image, based on a result of the determining.

Abstract: Disclosed embodiments integrate a camera into an intraoral mirror. Integrating a camera into an intraoral mirror provides an efficient way to record and display what is visible to the healthcare provider in the mirror.