Disclosed are techniques for automated analysis and assessments of contrast medium absorption phases in contrast medium based medical images. A target image set includes a plurality of medical images acquired to image a plurality of contrast medium absorption phases. For the images of the target image set, a set of contrast medium absorption phase probabilities are determined corresponding to likelihoods that a given image corresponds to a given contrast medium absorption phase. The determined sets of contrast medium absorption phases are compared against a reference set of contrast medium absorption phases to determine differences to determine a set of matching scores indicative of how closely the contrast medium absorption phases of the target image set align with the plurality of contrast medium absorption phases as compared to the reference set of contrast medium absorption phases.

A method is provided for determining a navigation image displaying features of a region of interest of a patient, (e.g., used during a medical intervention). The method includes determining a first subtraction image by recording a first X-ray image with an X-ray device and subtracting a mask image. The method also includes determining a second subtraction image by recording a second X-ray image with the X-ray device and by subtracting the mask image or a further mask image. Additionally, the navigation image is determined by superimposing the first and the second subtraction image. At least one of the subtraction images is preprocessed before the superimposition by transfer from a gray-value space into a color space that is different from a color space of the other subtraction image. The navigation image is determined in color and/or the dynamics of at least one of the subtraction images are compressed.

A medical information processing device according to an embodiment includes processing circuitry configured to acquire a plurality of X-ray images including a device inserted into a body of a subject, suppress movement of a characteristic portion characterized in a shape that is positioned distant from a distal end of the device among the X-ray images, and output the X-ray images in which movement of the characteristic portion is suppressed.

Techniques for processing images to be used for more accurate measurement of biological processes such as cell migration, as well as techniques for measuring cell migration. A method for processing microscopic images includes generating a smoothed image for a raw image by applying a smoothing filter to the raw image, wherein the raw image shows a plurality of cells and a background; generating a high pass filter image by dividing the raw image by the smoothed image; and transforming the high pass filter image into a transformed image by augmenting the spatial frequency of the plurality of cells shown in the high pass filter image with respect to the background.

In an approach for classifying regions of tissue captured in multispectral videos into medically meaningful classes using GPU accelerated perfusion estimation, a processor receives one or more multispectral videos of a subject tissue of a patient. A processor extracts one or more fluorescence time series profiles from the one or more multispectral videos. A processor estimates one or more sets of perfusion parameters based on the one or more fluorescence time series profiles. A processor inputs one or more feature vectors into a classifier, wherein the one or more feature vectors are derived the one or more sets of perfusion parameters. A processor receives a classification result for each of the one or more feature vectors, wherein the classification result comprises a set of medically relevant labels for each of the one or more feature vectors with a level of certainty for each label of the set of medically relevant labels.

A dynamic image control apparatus includes a hardware processor. The hardware processor obtains a plurality of frame images showing a dynamic state of a subject, identifies, from the plurality of frame images, a movement decrease region of a predetermined structure by user input or detection from the plurality of frame images, and performs control to attach accessory information to the plurality of frame images. The accessory information indicates the movement decrease region.

A medical scan artifact detection system is operable to receive a medical scan of a patient. Artifact detection data is generated by executing an artifact detection function on the medical scan, where the artifact detection data indicates at least one artifact detected in the medical scan that includes a motion artifact or a nipple shadow. A notification is generated for display via a display device, where the notification indicates the at least one artifact.

Disclosed is an automatic depression detection method using audio-video, including: acquiring original data containing two modalities of long-term audio file and long-term video file from an audio-video file; dividing the long-term audio file into several audio segments, and meanwhile dividing the long-term video file into a plurality of video segments; inputting each audio segment/each video segment into an audio feature extraction network/a video feature extraction network to obtain in-depth audio features/in-depth video features; calculating the in-depth audio features and the in-depth video features by using multi-head attention mechanism so as to obtain attention audio features and attention video features; aggregating the attention audio features and the attention video features into audio-video features; and inputting the audio-video features into a decision network to predict a depression level of an individual in the audio-video file.

Systems and methods are provided for multi-schema analysis of patient specific anatomical features from medical images. The system may receive medical images of a patient and metadata associated with the medical images indicative of a selected pathology, and automatically classify the medical images using a segmentation algorithm. The system may use an anatomical feature identification algorithm to identify one or more patient specific anatomical features within the medical images by exploring an anatomical knowledge dataset. A 3D surface mesh model may be generated representing the one or more classified patient specific anatomical features, such that information may be extracted from the 3D surface mesh model based on the selected pathology. Physiological information associated with the selected pathology for the 3D surface mesh model may be generated based on the extracted information.

A physiological information detection system includes an image-capturing unit, an image-processing unit and a data-transmitting unit. The image-capturing unit is provided to capture a series of images of head portions and connects with the image-capturing unit to receive the captured images. The image-processing unit is operated to process the captured images and to trace a head portion area and a neck portion area thereof in the processed images. The image-processing unit is further operated to process the captured images to retrieve temperature data from the selected head portion area and the selected neck portion area. The image-processing unit is further operated to convert variations of the temperature data into estimated pulse data. The data-transmitting unit connects with the image-processing unit to transmit the estimated pulse data to a predetermined device.