Abstract: An image calibration method and device. A deviation compensation coefficient of each pixel is calculated according to image data generated by strong and weak lighting parameters, and the deviation compensation coefficient is used to calibrate data of each image pixel collected and output by an image sensing unit. Therefore, the influence of inconsistency of each photosensitive element of the image sensing unit on the image greyscale can be eliminated, so that the effect of document medium image recognition is increased. The method in the embodiments of the present invention comprises: S1, acquiring a strong lighting parameter of each photosensitive element within a long exposure time and a weak lighting parameter thereof within a short exposure time; S2, acquiring image data of a sheet medium; and S3, according to the strong lighting parameter, the weak lighting parameter and the image data, calculating the calibrated image data of the sheet medium.

Abstract: Disclosed is a method for measuring movement and/or deformation of a study part subjected to an external stress, the method implementing a color digital image acquisition device and image correlation unit. The method includes: acquisition (250) of a plurality of color digital images of the surface of the study part by way of the color digital image acquisition device during the application of an external stress on the study part, and processing (260) of the color digital images acquired in the step of acquisition of a plurality of color digital images so as to highlight contrasting details on variable scales.

Abstract: A method for verifying authenticity of a monitoring signal includes employing a multitude of actuators to impact a physical environment with individual signals, wherein the individual signals originate from the actuators and are directed to the physical environment; observing, via at least one sensor device, the physical environment so as to record the monitoring signal, wherein the monitoring signal represents a combined impact of the individual signals on the physical environment; and comparing the monitoring signal with an expected signal to determine a degree of similarity between the monitoring signal and the expected signal, wherein the expected signal is computed on the basis of one or more predetermined templates, wherein the predetermined templates are previously generated in a secret initialization procedure in such a way that the impact on the physical environment for each of the individual signals is separately recorded as a template by the sensor device.

Abstract: The present invention relates a segmentation apparatus (10) for interactively segmenting blood vessels (2) in angiographic image data (3). The segmentation apparatus (10) comprises a significant location determining unit (11) for determining one or more locations of a current segmentation (4) of the blood vessels (2) in the angiographic image data (3) as significant locations (5) at which the current segmentation (4) has a predetermined influence on a value of a blood flow parameter that is calculated based on the current segmentation (4), and a display unit (12) for displaying the significant locations (5) to an operator. Thereby, the operator can be guided to focus his/her segmentation efforts to those locations of the current segmentation (4) that are most relevant for the accuracy of the calculation of the value of the blood flow parameter. This may ease the burden on the operator during the segmentation procedure.

Abstract: Deconvolution systems and methods based on cornea smoothing can be used to obtain an ablation target or treatment shape that does not induce significant high order aberrations such as spherical aberration. Exemplary ablation targets or treatment shapes can provide a post-operative spherical aberration that is equal to or below a naturally occurring amount of spherical aberration.

Abstract: A method is for segmenting an object in a medical image with a plurality of iteration steps. In an embodiment of the method, each iteration step includes generating a plurality of patches, a portion of the input image and a patch location being assigned to each patch, the patch location being indicative of the location of the portion of the input image relative to the input image. For each patch of the plurality of patches, the method includes determining a vote location based on the portion of the input image assigned to that patch and determining a target location based on the vote location and the patch location assigned to that patch. Finally, in an embodiment the method includes generating a vote map, each patch of the plurality of patches contributing to a pixel value at the target location of the patch in the vote map.

Abstract: First imaging means 60 creates a state image by capturing a state occurring in a first range. Second imaging means 70 creates a monitoring target image by capturing a monitoring target present in a second range. Specific state detection means 81 detects a specific state from the state image. Monitoring target analysis means 82 analyzes a status of a monitoring target, using the state image from which the specific state is detected. Monitoring target feature extraction means 85 extracts, from the monitoring target image, a feature used for specifying the monitoring target, based on the status of the monitoring target.

Abstract: The present invention relates to lung measurement. In order to provide enhanced information about a patient that facilitates further assessment steps, 2D X-ray image data of a patient's chest is provided, and the image data is segmented to identify lung structures to provide segmented image data separated from un-segmented areas. Further, spatial lung volume information is extracted from the image data using the segmented image data derived from the image data. Still further, lungs symmetry information is determined using the extracted spatial lung volume information. Finally, the lungs symmetry information is provided to a user. For example, a 2D X-ray image data of a patient's chest is provided (84) and a lungs mask image is formed (86) after the step of segmenting the input image data. Then, the lungs mask image is used to define areas, within which a predetermined adaptation is applied (88) to the original 2D X-ray image data producing a thorax mask image.

Abstract: A method of monitoring the amount of time spent in a specified area by an individual comprises employing a first camera to automatically create one or more entrance images, each entrance image containing a face of an entering individual that passes a first location, and storing each entrance image in a database along with a corresponding entrance time that the entering individual passed the entrance location. An exit image is compared to the entrance images in the database to identify a matching entrance image containing the same face as the exit image. A stay time is then determined for the exiting individual by determining the difference between the entrance time corresponding to the matching entrance image and the exit time.

Abstract: Methods and systems for obtaining a probabilistic diagnosis based on medical images of a patient are disclosed. In exemplary embodiments, such methods include the steps of scanning some or all of a patient to obtain a medical image; evaluating the medical image for one or more designated key features; assigning discrete values to the one or more designated key features to form a patient scan key feature pattern; and transmitting the values of the one or more designated key features to a processor programmed to match the patient scan key feature pattern to one or more known disease-specific key feature patterns to create a probabilistic diagnosis and transmit the probabilistic diagnosis to a user. Associated systems include a medical imaging device that is capable of producing a medical image of some or all of a patient and a processor programmed to create a probabilistic diagnosis.

Abstract: An image processing apparatus, a method, and a program for allowing cells to be quantitatively observed. A computer obtains a cell membrane image obtained by performing fluorescent observation on a cell membrane of a cell serving as a sample and a tricellular tight junction (tTJ) image obtained by performing fluorescent observation on a protein localized in a tTJ of the cell. The computer derives the size of area of a region of the cell by identifying the region of each cell from the cell membrane image, derives the size of area of the region of the protein localized in the cell from the tTJ image, and dividing the obtained size of area of the region of the protein by the size of area of the region of the cell, thus calculating an index of adhesion strength of the cells. The invention can be applied to an observation system.

Abstract: An image processing device includes an input unit and an alignment unit. The input unit inputs a cell shape image and a fluorescence image. The cell shape image shows a shape of a cell in a tissue section. The fluorescence image shows expression of a specific protein as a fluorescent bright point in a region same as a region in the tissue section. The alignment unit aligns the cell shape image and the fluorescence image based on an information source detected in both the cell shape image and the fluorescence image.

Abstract: Measuring the number of glomeruli in the entire, intact kidney using non-destructive techniques is of immense importance in studying several renal and systemic diseases. In particular, a recent Magnetic Resonance Imaging (MRI) technique, based on injection of a contrast agent, cationic ferritin, has been effective in identifying glomerular regions in the kidney. In various embodiments, a low-complexity, high accuracy method for obtaining the glomerular count from such kidney MRI images is described. This method employs a patch-based approach for identifying a low-dimensional embedding that enables the separation of glomeruli regions from the rest. By using only a few images marked by the expert for learning the model, the method provides an accurate estimate of the glomerular number for any kidney image obtained with the contrast agent. In addition, the implementation of our method shows that this method is near real-time, and can process about 5 images per second.

Abstract: The invention comprises using a photodetector that it sensitive in the MWIR band, performing image differencing on two successive images at a time, and defining thresholds for said differences in order to extract only those exceeding the threshold used.

Abstract: Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.

Abstract: A system, apparatus and method for mesh registration including an extraction of a preoperative anatomical mesh from a preoperative anatomical image based on a base topology of an anatomical mesh template, an extraction of an intraoperative anatomical mesh from an intraoperative anatomical image based on a preoperative topology of the preoperative anatomical mesh derived from the base topology of an anatomical mesh template, and a registration of the preoperative anatomical image and the intraoperative anatomical image based on a mapping correspondence between the preoperative anatomical mesh and the intraoperative anatomical mesh established by an intraoperative topology of the intraoperative anatomical mesh derived from the preoperative topology of the preoperative anatomical mesh.

Abstract: The present disclosure provides methods for colorizing and/or standardizing a medical image, comprising, for example, the steps of (i) receiving, in an image processing unit, digital image data obtained by an image capture device, wherein the digital image data includes a medical image; (ii) analyzing the data with the image processing unit to identify a region of interest; (iii) segmenting said region of interest; (iv) obtaining a measure of the pixel intensities in the segmented region of interest; (v) selecting an optimized color spectrum from a plurality of color spectra using the result of the measure of the pixel intensities in the segmented region of interest; (vi) colorizing the digital image data by mapping the selected color spectrum to the region of interest; and (vii) displaying the colorized medical image.

Abstract: The invention relates to detecting and tracking objects in a sequence of images. In particular, a method, software and system for tracking a non-rigid object in a plurality of images. Initially, a first set of parameters for a parameterized shape model are generated (410) based on a first image. Then a second set of parameters are generated (415) for the parameterized shape model by fitting the parameterized shape model to the object in a second image of the plurality of images. This fitting is according to (i) the one or more constraints defined independently of the object or (ii) the first set of parameters. Also, the first and second sets of parameters define a tracking of the non-rigid object between the first and second images.

Abstract: A system includes a three-dimensional camera and a processor communicatively coupled to the three-dimensional camera. The processor is operable to determine a first and second edge of a dairy livestock. The first edge includes an inner portion of a first hind leg and a first portion of an udder of the dairy livestock. The second edge includes an inner portion of a second hind leg and a second portion of the udder of the dairy livestock. The processor calculates a reference point associated with the udder of the dairy livestock based at least in part upon the first edge and the second edge. A robotic attacher moves toward the udder of the dairy livestock based at least in part upon the calculated reference point.

Abstract: Methods and systems are provided for multi-window imaging. In one embodiment, a method comprises segmenting an image reconstructed from acquired projection data into segments, converting pixel values based on a mapping for each segment to generate converted segments, and outputting, to a display device, a composite image comprising a combination of the converted segments. The composite image includes a border delineating the converted segments. In this way, multiple windows collectively covering a large dynamic range may be combined into a single image.