Systems and methods of predicting future medical events are based on the processing of medical image. The prediction of premature birth and estimation of gestational age based on ultrasound images are presented as illustrative examples. The new abilities to estimate the probability of future medical events, before they otherwise could be predicted, provides new avenues for the development of preventative treatments.

A method, computer system, and a computer program product for simulated follow-up imaging is provided. The present invention may include receiving a set of longitudinal imaging exam data associated with a patient. The received set of longitudinal imaging exam data may correspond to a series of repeated examinations of the patient conducted over time. The present invention may also include generating, using a trained learning model, a synthetic medical image associated with the patient. The generated synthetic medical image may correspond to a simulated future imaging exam of the patient predicted based on at least a portion of the series of repeated examinations of the patient conducted over time.

A medical scan interface feature evaluator system is operable to receive a set of responses from each of a set of client devices, where each set of responses is generated based on a corresponding client device displaying each of the set of medical scans in conjunction with at least one interface feature indicated in an image-to-prompt mapping. Response score data is generated for each response of the set of responses received from each of the set of client devices by comparing each response to truth annotation data of a corresponding medical scan of the set of medical scans indicated by the image-to-prompt mapping. Interface feature score data corresponding to each user interface feature in the set of user interface features is generated based on aggregating corresponding response score data. A ranking of the set of user interface features is generated based on the interface feature score data.

In a medical image processing apparatus including a processor, the processor sequentially acquires time-series medical images and causes a display unit to sequentially display the acquired medical images. Further, the processor performs a process of acquiring, based on the acquired medical images, information related to a position of a region of interest in the medical images and classifying the region of interest into a class among a plurality of classes, and displays class information indicating the class of the classified region of interest such that the class information is superimposed at a position of the region of interest in a medical image displayed on the display unit. Further, the processor changes a relative position of the superimposed class information with respect to the region of interest, in accordance with an elapsed time from recognition of the region of interest.

At least one example embodiment relates to a computer-implemented method comprising receiving a plurality of medical images with a transmitting apparatus interface, determining a first base image, based on a first medical image, with a transmitting apparatus computing unit, transferring the first base image, determining a first change information item, based on the first medical image and a second medical image, with the transmitting apparatus computing unit, determining a first modified base image based on the first change information item and the first base image, checking at least one of the second medical image or the first modified base image, transferring the second medical image with the transmitting apparatus interface to the receiving apparatus interface based on the result of the checking.

A method for analysis of cellular contractions of cells comprises recording a sequence of images of the cells. The sequence comprises a first image and a second image. The position of points of note in the first image are determined. The position of the same points of note in the second image, and for at least one point of note of the first image, is determined. A correspondence is established between the point of note of the first image and a point of note of the second image. The movement of the point of note, between the first image and the second image, is determined by comparing the position of the point of note of the first image and the position of the corresponding point of note of the second image.

A reference part extracting unit extracts at least one reference part that is common in a first image and a second image, from each of the first image and the second image. A first position information deriving unit derives first position information indicating a relative position of at least one abnormal part specified in the first image, relative to the at least one reference part in the first image. A second position information deriving unit derives second position information indicating a relative position of at least one abnormal part specified in the second image, relative to the at least one reference part in the second image. A matching unit associates, on the basis of a difference between the first position information and the second position information, the abnormal part included in the first image and the abnormal part included in the second image with each other.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining a subset of brain data of a patient. One of the methods comprises providing connectivity data for presentation to a user, the connectivity data characterizing, for each pair of parcellations comprising a first parcellation and a second parcellation from a plurality of parcellations, a degree of correlation between the brain activity of the first parcellation and the brain activity of the second parcellation in the brain of a patient; determining one or more elements of interest in the connectivity data; determining one or more parcellations associated with elements of interest in the connectivity data; obtaining brain atlas data; determining a subset of the brain atlas data associated with the determined parcellations; and providing the subset of the brain atlas data to a user device for rendering the subset to the user.

There is provided a medical imaging processing device, comprising: at least one hardware processor executing a code for: iteratively generating instructions for iterative adjustment of presentation parameter(s) of a 2D frame of the 3D anatomical image presented on the display, for creating a sequence of adapted 2D frames of the 3D anatomical image, the instructions transmitted from the medical imaging processing device to a physical input interface of at least one of the client terminal and display, for each respective 2D frame: capturing the respective 2D frame from video signals transmitted from the client terminal to the display, analyzing the respective captured 2D frame for extraction of a 2D anatomical image, analyzing the respective captured 2D frame to identify metadata element(s), converting the metadata element(s) into converted metadata value(s), and formatting the extracted 2D anatomical images and associated converted metadata values for reconstruction of the 3D anatomical image.

Methods, systems, and computer programs for monitoring skin condition of a person. In one aspect, a method can include obtaining data representing a first image, the first image depicting skin from at least a portion of a body of a person, generating a severity score that indicates a likelihood that the person is trending towards an increased severity of an auto-immune condition or trending towards a decreased severity of an auto-immune condition, comparing, the severity score to a historical severity score, wherein the historical severity score is indicative of a likelihood that a historical image of the user depicts skin of a person having the auto-immune condition, and determining based on the comparison, whether the person is trending towards an increased severity of the auto-immune condition or trending towards a decreased severity of the auto-immune condition.