Abstract: A computer-implemented method for detecting at least one feature of interest in images captured with an imaging device includes: receiving an ordered set of images and analyzing one or more subsets of the ordered set using a local spatio-temporal processing module. The local spatio-temporal processing module determines presence of characteristics related to the feature of interest in each image of each subset of images and annotates the subset of images. The method also includes processing a set of feature vectors of the ordered set of images using a global spatio-temporal processing module to refine the determined characteristics associated with each subset of images, and calculate one or more values for each image using a timeseries analysis module, the values being representative of the feature of interest and calculated using the refined characteristics associated with each subset of images and spatio-temporal information.

Abstract: A computer-implemented method for detecting at least one feature of interest in images captured with an imaging device includes: receiving an ordered set of images and analyzing one or more subsets of the ordered set using a local spatio-temporal processing module. The local spatio-temporal processing module determines presence of characteristics related to the feature of interest in each image of each subset of images and annotates the subset of images. The method also includes processing a set of feature vectors of the ordered set of images using a global spatio-temporal processing module to refine the determined characteristics associated with each subset of images, and calculate one or more values for each image using a timeseries analysis module, the values being representative of the feature of interest and calculated using the refined characteristics associated with each subset of images and spatio-temporal information.

Abstract: A computer-implemented method for detecting at least one feature of interest in images captured with an imaging device includes: receiving an ordered set of images and analyzing one or more subsets of the ordered set using a local spatio-temporal processing module. The local spatio-temporal processing module determines presence of characteristics related to the feature of interest in each image of each subset of images and annotates the subset of images. The method also includes processing a set of feature vectors of the ordered set of images using a global spatio-temporal processing module to refine the determined characteristics associated with each subset of images, and calculate one or more values for each image using a timeseries analysis module, the values being representative of the feature of interest and calculated using the refined characteristics associated with each subset of images and spatio-temporal information.

Abstract: A computer-implemented system is provided that includes at least one processor that is adapted to analyze a plurality of frames from a real-time video to identify frames during which an operator is interacting with an image device to examine areas of a patient. The at least one processor is further configured to generate, from the identified frames, data representations of a first area examined by the operator interacting with the image device and further generate data representations of one or more further areas examined by the operator interacting with the image device.

Abstract: In one implementation, a computer-implemented system is provided for real- time video processing. The system includes at least one memory configured to store instructions and at least one processor configured to execute the instructions to perform operations. The at least one processor is configured to receive real-time video generated by a medical image system, the real-time video including a plurality of image frames, and obtain context information indicating an interaction of a user with the medical image system. The at least processor is also configured to perform an object detection to detect at least one object in the plurality of image frames and perform a classification to generate classification information for at least one object in the plurality of image frames. Further, the at least one processor is configured to perform a video manipulation to modify the received real-time video based on at least one of the object detection and the classification.

Abstract: A computer-implemented system is provided that receives a real-time video captured from a medical image device during a medical procedure. The real-time video may include a plurality of frames. The system may be adapted to detect an object of interest in the plurality of frames and apply one or more neural networks configured to identify a plurality of characteristics of the detected object of interest, such as classification, size, and/or location. In some embodiments, the system is adapted to identify, based on one or more of the plurality of characteristics, a medical guideline and present, in real-time on a display device during the medical procedure, information for the medical guideline.

Abstract: An apparatus for recording skin lesions on a patient comprises an apparatus for acquiring images and a control and processing unit connected to the apparatus so as to acquire and process a plurality of images of the patient positioned in different angular positions with respect to the apparatus. The control and processing unit comprises a processing block which receives at its input the plurality of images acquired by the apparatus and provides at its output a two-dimensional image obtained as a planar development of a three-dimensional image of the patient calculated in the processing block from the plurality of images acquired. By means of extraction of characteristics indicative of the lesions from the two-dimensional image it is possible to classify the lesions in an automatic or semi-automatic manner. A method for electronically recording skin lesions on a patient is also described.