Abstract: The invention generally relates to analytical and monitoring systems useful for analyzing and measuring cells and biological samples. More particularly, the invention provides systems and methods for internal calibration and focus reference for cytometry imaging.

Abstract: Various approaches to image enhancement are disclosed. In one approach, an image to be enhanced and a boundary map are received. A field value array is made using the boundary map and the received image. For each field represented in the field value array, pixel values obtained from the received image are aggregated. An enhanced image is generated as output by performing a rereasterization using the aggregated values. In another approach, an image to be enhanced and an edge map are received. Edge-masked derivative matrices are constructed. The edge-masked derivative matrices are used to iteratively solve a series of linear equations, wherein solutions to the linear equations minimize an increasingly accurate quadratic approximation of a penalty function that measures a total amount of variation in a function, and a derivation of the function from the image. A vector result of the iterative solution is transformed into a raster image.

Abstract: A computer implemented method for determining a centerline of a three-dimensional tubular structure is described. The method includes providing an edge-detected data set of voxels that characterize a boundary of the tubular structure according to a three-dimensional voxel data set for the tubular structure. A gradient field of a distance transformation is computed for the edge-detected dataset. A voxel data set corresponding to a centerline of the tubular structure is computed according to derivative of gradient field.

Abstract: A method comprising: training a price tag detector, comprising a gross feature detector and a classifier, to automatically detect a price tag in an image, by: a) training the gross feature detector using supervised learning with labeled images, and b) training the classifier using a two-phase hybrid learning process comprising: c) applying an initial supervised learning using the labeled images, yielding a semi-trained version of the classifier, and d) applying a subsequent unsupervised learning using unlabeled images, yielding a fully trained version of the classifier, wherein applying the unsupervised learning comprises: for each unlabeled image: i) detecting multiple price tag hypotheses using the gross feature detector, ii) classifying each price tag hypothesis using the semi-trained classifier, ii) rating each classification based contextual data extracted from the unlabeled image, iv) retraining the semi-trained classifier with the rated classifications, and repeating steps ii) through iv) until the rec

Abstract: Systems and methods of detecting irregular events include the extraction of values for measure in each of a plurality of notifications. The extracted values are stored in a measures database and a distribution is calculated for the values of each of the measures. The extracted values are compared to the calculated distributions to determine if an irregular event has occurred. An irregularity alert is produced if an irregular event has occurred.

Abstract: Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.

Abstract: An ophthalmologic examination apparatus capable of accurately discriminating a boundary between layers indicated by an operator (user) among boundaries of an object to be inspected, when the operator manually changes a position of information designating boundary of layers includes: an acquiring unit configured to acquire a tomographic image of an object to be inspected; a display control unit configured to cause a display unit to display the tomographic image and information designating boundary of layers in the tomographic image; and an adjustment unit configured to adjust, in a case where a boundary of layers is indicated in the displayed information, contrast of the tomographic image such that a brightness difference between layers corresponding to the indicated boundary in the tomographic image becomes large.

Abstract: The image processing device includes a gradation correction unit (gamma correction processing unit 33) which performs gradation correction, a restoration processing unit, a sharpening processing unit, a sharpening and recovery control unit 37 which is able to adjust a restoration rate of restoration processing and a sharpening rate of sharpening processing by controlling the restoration processing unit and the sharpening processing unit, a sharpening and recovery control unit 37 which acquires a total sharpening and restoration rate based on the restoration rate and the sharpening rate and one rate of the restoration rate and the sharpening rate and calculates the other rate of the restoration rate and the sharpening rate based on the total sharpening and restoration rate, and a brightness information acquisition unit. The sharpening and recovery control unit adjusts the restoration rate and the sharpening rate according to acquired brightness information.

Abstract: Methods and systems for processing a set of images are described. In accordance with this disclosure, images are registered and an analysis is performed in view of one or more constraints (such as constraints based upon anatomical or physiological considerations). Weighting factors are determined based on the analysis. The weighting factors are used in subsequent processing of the registered (and/or unregistered) images and/or to formulate a visualization that conveys the degree of confidence in the motion estimation used in the registration process.

Abstract: Certain aspects of an apparatus and method for automatic ER/PR scoring of tissue samples may include for determining a cancer diagnosis score comprising identifying a positive stained nucleus in a slide image of the tissue sample, identifying a negative stained nucleus in the slide image, computing a proportion score based on number of the positive stained nucleus identified and number of the negative stained nucleus identified and determining the cancer diagnosis score based on the proportion.

Abstract: Systems, devices, and methods are presented for segmenting an image of a video stream with a client device by accessing a set of images within a video stream, identifying an object of interest within one or more images of the set of images, and detecting a region of interest within the one or more images. The systems, devices, and method identify a first set of median pixels in a first portion of the object of interest and a second set of median pixels in a second portion of the object of interest. The systems, devices, and methods determine a polyline approximating the first and second sets of median pixels and generate a model for the polyline.

Abstract: Described is a technology by which an image such as a stitched panorama is automatically cropped based upon predicted quality data with respect to filling missing pixels. The image may be completed, including by completing only those missing pixels that remain after cropping. Predicting quality data may be based on using restricted search spaces corresponding to the missing pixels. The crop is computed based upon the quality data, in which the crop is biased towards including original pixels and excluding predicted low quality pixels. Missing pixels are completed by using restricted search spaces to find replacement values for the missing pixels, and may use histogram matching for texture synthesis.

Abstract: A metadata extraction machine accesses an image that depicts an item. The item depicted in the image may have an attribute that describes a characteristic of the item and an attribute descriptor that corresponds to the attribute of the item and specifies a value of the attribute. The metadata extraction machine performs an analysis of the image. The analysis may include identifying the attribute descriptor corresponding to the attribute based on image segmentation of the image. The metadata extraction machine transmits a communication to a device of a user based on the identifying of the attribute descriptor corresponding to the attribute of the item depicted in the image.

Abstract: As the use of facial biometrics expands in the commercial and government sectors, the need to ensure that human facial examiners use proper procedures to compare facial imagery will grow. Human examiners have examined fingerprint images for many years such that fingerprint examination processes and techniques have reached a point of general acceptance for both commercial and governmental use. The growing deployment and acceptance of facial recognition can be enhanced and solidified if new methods can be used to assist in ensuring and recording that proper examination processes were performed during the human examination of facial imagery.

Abstract: Certain aspects of an apparatus and method for automatic ER/PR scoring of tissue samples may include for determining a cancer diagnosis score comprising identifying a positive stained nucleus in a slide image of the tissue sample, identifying a negative stained nucleus in the slide image, computing a proportion score based on number of the positive stained nucleus identified and number of the negative stained nucleus identified and determining the cancer diagnosis score based on the proportion.

Abstract: A computer vision system (100) operates to monitor an environment (e.g., such as a restaurant, store or other retail establishment) including a resource located therein (e.g., such as a restroom, a dining table, a drink, condiment or supply dispenser, a trash receptacle or a tray collection rack). The system includes: an image source or camera (104) that supplies image data (130) representative of at least a portion of the environment monitored by the system, the portion including the resource therein; and an event detection device (102) including a data processor (112) and operative to detect an event involving the resource. Suitably, the event detection device is arranged to: (i) be selectively configurable by a user to define the event involving the resource; (ii) receive the image data supplied by the image source; (iii) analyze the received image data to detect the defined event; and (iv) output a notification in response to detecting the defined event.

Abstract: Image processing for productivity applications is provided. An image may be received by a computing device. The computing device may detect the edges comprising the received image and adjust the image based on a skew state of the detected edges. The computing device may then process the adjusted image to correct imbalances. The computing device may then assign an image classification to the processed image. The computing device may then adjust the processed image based on the assigned image classification.

Abstract: A first image is received. An initial label is assigned to at least some pixels in the first image, including by assigning a first label to a first pixel. A determination is made, based at least in part on labels of spectral neighbors of the first pixel, that the first pixel's label should be replaced with a different label. The first pixel's label is updated with the different label.

Abstract: Methods and systems for controlled administration of a tracer and quantification of uptake of the tracer by a target organ are described. The method includes administering a tracer to a patient and imaging at least two regions of the patient's body that cannot be imaged simultaneously. An input function for the tracer can be determined by imaging a first region of the patient's body during selected times, and using an injector to administer the tracer in a manner that accurately estimates the input function when this first region is not being imaged. One or more additional regions of the body may then be imaged to create data that may be used to estimate the input function. One or more parameters may then be estimated from each additional region of the body based on the input function and the imaging data gathered from each region.

Abstract: System and method for detecting a fraudulent activity at a barcode scanner is disclosed. The method issues an alert when the fraudulent activity is confirmed by comparing the visual signature of the item being transacted over the checkout terminal to the model visual signature. The model visual signature is obtained by averaging the collection of visual signature of the item gathered over a period of time. A human validation via a remote processor is employed to confirm the fraudulent activity verified by a computer.