An image processing apparatus (10) is disclosed that comprises a processor arrangement (16) adapted to receive image data corresponding to a region of interest (1) of a patients cardiovascular system, said image data comprising a temporal sequence (15) of intravascular ultrasound images acquired (150) at different phases of at least one cardiac cycle of said patient, said intravascular ultrasound images imaging overlapping volumes of the patients cardiovascular system; implement a spatial reordering process of said temporal sequence of intravascular ultrasound images by evaluating the image data to select at least one spatial reference (6, V.sub.ref) associated with said temporal sequence of intravascular ultrasound images; estimating a distance to the at least one spatial reference for each of the intravascular ultrasound images of said temporal sequence; and reordering said temporal sequence of intravascular ultrasound images into a spatial sequence of intravascular ultrasound images based on the estimated distances; and generate an output comprising said spatial sequence of intravascular ultrasound images. Also disclosed are a method and computer program product to configure an image processing apparatus accordingly.

A compartmentalized dynamic anatomic atlas is disclosed, comprising static atlas data comprising spatial element data and element representation data, wherein the spatial element data describes spatial properties of a spatial atlas element and wherein the element representation data describes representational properties assignable to the spatial atlas element, the atlas further comprising dynamic atlas data comprising information on a dynamic property which information is respectively linked to the spatial atlas element.

An image classification method is provided to an electronic device. The method includes: receiving a target image and a reference image about the target image, the target image being a medical image; determining a first image feature of the target image and a second image feature of the reference image; fusing the first image feature and the second image feature to determine a to-be-classified image feature; and determining, by using the to-be-classified image feature, a probability that the target image belongs to a preset category.

A method, and corresponding apparatus, for identifying a feature in an image comprises determining a plurality of characteristic values for each pixel or group of pixels within the image, and determining a confidence value for a target area of the image on the basis of the plurality of characteristic values of the pixels within the target area. Each of the plurality of characteristic values relates to a different characteristic of the feature. The confidence value is indicative of whether the feature is represented by the target area of the image.

The present disclosure generally relates to a computer implemented method for adaptively selecting at least one wound product for a patient, for example adapted to take into account a healing trajectory determined for a wound of the patient. The present disclosure also relates to a corresponding computer system and computer program product.

Systems, methods, apparatuses, and computer program products for contact-free heart rate monitoring and/or measurement are provided. One method may include receiving video(s) that include visual frame(s) of individual(s) performing exercises, detecting some exposed skin from the video(s), and performing motion compensation to generate color signals for the exposed skin to precisely align frames of the exposed skin. The method may also include generating the color signals by estimating a skin color for each frame by taking a spatial average over pixels of a cheek of the face(s) for R, G, and B channels, respectively, applying an operation to remove remaining motion traces from the frames such that the heart rate traces dominate, and extracting and/or outputting the heart rate of the individuals using a frequency estimator of the skin color signals.

Provided is an image processing device including a hardware processor. The hardware processor: obtains a static image and a dynamic image of a same subject by radiographic imaging; detects, on the static image, a first analysis target area; detects, on the dynamic image, a second analysis target area corresponding to the first analysis target area; analyzes the second analysis target area of the dynamic image to generate a functional information representative from change caused by biological motion; deforms and positions the second analysis target area so that the second analysis target area corresponds to the first analysis target area; overlays the functional information representative of the deformed and positioned second analysis target area on the static image.

An image display apparatus includes a display that displays multiple dynamic images and a hardware processor. The multiple dynamic images include at least two dynamic images and show a target region. The hardware processor enlarges/reduces at least one of the at least two dynamic images at an enlargement/reduction ratio that equalizes a size of the target region in a specific state among the at least two dynamic images, and causes the display to display the at least two dynamic images.

An analysis method and a diagnostic device, enabling one to determine whether a longitudinal melanonychia is caused by a malignant melanoma or a benign nevus by correcting color variation in a dermoscopic image through standardization of color balance without depending on an imaging device or an operator; and a computer program for allowing a computer to function as the diagnostic device. Proposed is a structure including: an image reading step of reading a color image of a longitudinal melanonychia or an affected skin site of a subject as a digital color image; an image processing step involving an image size conversion step of converting the whole size of the digital color image into a preset size through pixel size conversion, and a region of interest (ROI)-extraction step of extracting an ROI required for the diagnosis from the digital color image; a chromatic adaptation transformation step of controlling the color balance of the digital color image data through chromatic adaptation transformation; and a discrimination index (DI) calculation step of determining a DI value using the image after the chromatic adaptation transformation.

An image processing apparatus supports detection of pathological change over time in portion of a captured region commonly included in a first image and a second image, the first image and the second image acquired by capturing a subject at different respective times. The image processing apparatus includes an acquisition unit configured to acquire a subtraction image of the first image and the second image representing the pathological change over time as a difference and a recording unit configured to record information indicating said portion using a name different from a name of the commonly included region in a storage unit in association with the subtraction image.