Abstract: An image processing system includes a modified area deciding unit, a modified area correlation deciding unit, a display selecting unit and a displaying unit. The modified area deciding unit executes processing of deciding a modified area containing a pixel area, which is distinguished as postscript information, based on input image data. The modified area correlation deciding unit specifies a related information area corresponding to the modified area, which is decided by the modified area deciding unit. The modified area correlation deciding unit executes processing of deciding a correlation between mutual areas. The display selecting unit selects the postscript information and related information of the postscript information, based on the correlation between the mutual areas, which are decided by the modified area correlation deciding unit. The displaying unit executes processing of displaying output data in response to a selecting mode of the display selecting unit.

Abstract: Provided is a method for generating views of tomographic image data. At least one view of an object area is generated by image filtering from tomographic CT image data by using a modulation transfer function and coordinate information. A filter algorithm is used for the image filtering and, if appropriate, further view parameters required for generating the view may be stored in a view file assigned to the CT image data. The view file is called up, and the filter algorithm as well as, if appropriate, the further view parameters are applied to the CT image for the purpose of renewed generation of the view.

Abstract: A position calculation apparatus calculates a positional relationship between an image pickup device, which is for taking an image of first and second imaging targets, and at least one of the first and second imaging targets. The position calculation apparatus obtains a first size, which indicates a size of a target image of the first imaging target in the image taken by the image pickup device, and a second size which indicates a size of a target image of the second imaging target in the image taken by the image pickup device. Then, based on the first and second sizes, the position calculation apparatus calculates the positional relationship between the image pickup device and the first and second imaging targets.

Abstract: An efficient method and system of contouring target volumes and normal tissues at risk using an expert case as interactive tutorial reference for radiation therapy treatment plan is disclosed. Target volume contours based on guidance from a disease-matched expert case is selected by the user. The second imaging data set of a new patient is then displayed and linked with expert's case in a the slice-by-slice and side-by-side fashion and at comparable field-of-view angles. Users can generate the target volume contours on the new patient using expert case as tutorial guidance or overlaying the expert contours onto the new patient's imaging data set followed by reforming the target volume contours to fit the anatomical terrain of the patient. Users can then modify the target volume contours of their patient using expert case as tutorial guidance linked in a the slice-by-slice and side-by-side fashion and at comparable field-of-view angles.

Abstract: A scaling system for compressing a bitonal image that has print density control. A system is disclosed that comprises: a pixel reduction system that generates a scaled image by reducing pixel pairs down to single scaled pixel based on a set of scaling rules; and a line density control system that allows the scaled image to be made lighter, normal or darker by changing the scaling rules.

Abstract: A method of automatically generating an envelope of constraint points for a target region to optimize an inverse treatment plan by modifying the dose isocontour.

Abstract: Certain embodiments of the present application provide a method for imaging in a healthcare environment including receiving in an application a first feed, the first feed including historical patient image data; receiving in the application a second feed, the second feed including substantially live patient image data; and integrating in real-time in the application the first feed and the second feed to form a display representation, the display representation displayable on a display, and the display representation simultaneously including data corresponding to the first feed and the second feed.

Abstract: Background blurring is an effective way to both preserve privacy and keep communication effective during video conferencing. The present image background blurring technique is a light weight real-time technique to perform background blurring using a fast background modeling procedure combined with an object (e.g., face) detector/tracker. A soft decision is made at each pixel whether it belongs to the foreground or the background based on multiple vision features. The classification results are mapped to a per-pixel blurring radius image to blur the background. In another embodiment, the image background blurring technique blurs the background of the image without using the object detector.

Abstract: An image processing apparatus includes: a change region judging unit that performs a judging process including a pixel area discriminated to represent additional writing information on a change region according to input image data; a change region state judging unit that performs image analysis on an area judged by the change region judging unit to be a change region, and that judges presence/absence of additional writing information to be used to tamper; a warning display control unit adapted to set a display mode according to a result of judgment to enable additional writing information, which is highly likely to tamper, to be discriminated; and a display unit that performs an output data displaying process according to the display mode set by the warning display control unit.

Abstract: A method for improving a thoracic diagnostic image for the detection of nodules. Non-lung regions are removed from the diagnostic image to provide a lung image. Vessels and vessel junctions of the lung(s) in the lung image are enhanced according to a first-order partial derivative of each of a plurality of voxels of the lung image. A vessel tree representation is constructed from the enhanced vessels and vessel junctions. The vessel tree representation can be subtracted from the lung image to enhance the visibility of nodules in the lung(s).

Abstract: A method, system and program product for the detection of removed objects in video images is disclosed. An object (or objects) is within a fixed camera's FOV (Field of View), is designated to be monitored. If an object is not designated, an algorithm can be used to segment and identify all the objects in the image that is acquired by a fixed camera. In such case, all these objects can be monitored. A reference frame around the monitored object that also includes the surrounding background can be determined. The object can be extracted out of the reference frame, thereby creating a “reference with hole” image and an object reference image. The hole in the “reference with hole” image can be filled by either an in-painting algorithm or a texture synthesis algorithm depending on the complexity of the surrounding background.

Abstract: A method for computer-assisted interpretation of medical images that factor in characteristics of an individual performing the interpretation. The method automatically determines and/or incorporates prevalence-based computer analysis based on an estimated likelihood of a pathological state, e.g., a malignancy. A system implementing the method includes the calculation of features or other characteristics of images in a known database, calculation of features of an unknown case, calculation of the probability (or likelihood) of disease state, calculation of the modified computer output that includes the internal prevalence (or internal decision-making process) of the user (or group of users), and output of the result.

Abstract: A method for analyzing a medical image. The process: establishes a predetermined criteria; obtains data in a plane traverse the anatomical object; identifies a point disposed on the object in the plane; detects contour points of the object in the plane from the identified point; analyzes the obtained contour points to predict a subsequent point on the object and a tracing direction, such tracing direction being along the length of the object; determines a subsequent plane transverse the object, such predicted point being in the subsequent plane; repeats the process until the predetermined criterion is satisfied.

Abstract: An image processing device for a vehicle includes a radar for transmitting a radio wave outside of the vehicle and detecting an object in a first area outside of the vehicle by using a reflected wave of the transmitted radio wave; a camera for acquiring an image in a second area including the first area; and an image processing unit for processing the acquired image to detect, in the acquired image, the object detected by the radar. Visibility outside of the vehicle is detected based on result of detection of the radar and result of detection of the camera.

Abstract: An optical image measuring device which can form a highly reliable image even if an object moves during scanning of a signal light is provided. An optical image forming device 1 comprises: an interferometer that splits a low coherence light L0 into a signal light LS and a reference light LR and generates an interference light LC by overlaying the signal light LS reflected by a fundus oculi with the reference light LR reflected by a reference mirror 14; a CCD 34 which receives the interference light LC and outputs a detection signal; Galvanometer mirrors 22 and 23 to scan the signal light LS in a main scanning direction and a sub-scanning direction; and a computer 40 forming tomographic images G1 to Gm along the main scanning direction at different positions of the sub-scanning direction.

Abstract: The present invention is a processing system for identifying a string formed from a number of hand-written characters. The system includes a processor and memory, an input device and an output device, a bus connecting the processor, memory, input and output devices, as well as an external interface for connecting the bus to an external database. The processor is configured to perform the steps of determining character probabilities for each character in the string, each character probability representing the likelihood of the respective character being a respective one of a number of predetermined characters; and determining template probabilities for the string, each template probability representing the likelihood of the string corresponding to a respective one of a number of templates, each template representing a respective combination of character types.

Abstract: Certain embodiments of the present invention provide methods and systems for determine a level of significance of an image. Certain embodiments include selecting one or more parameters for use in determining a level of significance for an image, assigning a value to each of the one or more parameters, and determining the level of significance for the image based on the parameters and the values associated with each of the one or more parameters. One or more parameters may be weighted to affect determination of the level of significance. An offset may be added to the determination of the level of significance for the image. Parameters may include clinical relevance, diagnosis pattern, segmented area, number of pixels, and/or reading time for the image, for example.

Abstract: A system and method are provided for contrast-invariant registration of images, the system including a processor, an imaging adapter or a communications adapter for receiving an image data sequence, a user interface adapter for selecting a reference frame from the image sequence or cropping a region of interest (ROI) from the reference frame, a tracking unit for tracking the ROI across the image sequence, and an estimation unit for segmenting the ROI in the reference frame or performing an affine registration for the ROI; and the method including receiving an image sequence, selecting a reference frame from the image sequence, cropping a region of interest (ROI) from the reference frame, tracking the ROI across the image sequence, segmenting the ROI in the reference frame, and performing an affine registration for the ROI.

Abstract: Retinal images can be classified by selecting a classifier and a figure of merit for quantifying classification quality; selecting a transform to generate features from input data; using a recursive process of functional dissipation to generate dissipative features from the features generated according to the transform; computing the figure of merit for all of the dissipative features generated; searching for at least one of the dissipative features that maximize the figure of merit on a training set; and classifying a test set with the classifier by using the “at least one of the dissipative features.

Abstract: An image processing apparatus includes: an image reading unit that reads image information; a generating unit that generates new additional information to be added to the image information read by the image reading unit; an extracting unit that extracts, in a case where the image information read by the image reading unit includes existing additional information, the existing additional information; and an additional information processing unit that embeds the existing additional information and the new additional information in the image information.