Provided are an information processing apparatus, an information processing method, and a program capable of accumulating appropriate relearning data. An information processing apparatus includes an input unit that inputs input data to a learned model acquired in advance through machine learning using learning data, an acquisition unit that acquires output data output from the learned model through the input using the input unit, a reception unit that receives correction performed by a user for the output data acquired by the acquisition unit, and a storage controller that performs control for storing, as relearning data of the learned model, the input data and the output data that reflects the correction received by the reception unit in a storage unit in a case where a value indicating a correction amount acquired by performing the correction for the output data is equal to or greater than a threshold value.

A computer-implemented method for processing an electronic image may include receiving, by an artificial intelligence (AI) system at an electronic storage of the AI system, one or more digital whole slide images (WSIs) and extracting one or more vectors of features from one or more foreground tiles of tile images of the one or more digital WSIs. The method may include running a trained machine learning model on the one or more vectors of features and determining, based on an output of the trained machine learning model, whether one or more quality issues are present in the one or more digital WSIs.

At least one vascular tree supplying at least a part of the hollow organ in the computed tomography dataset is segmented, and a tree structure up to an order possible based on the blood vessel segmentation result is determined from a blood vessel segmentation result. Perfusion information for each edge in the tree structure is assigned as at least one of the computed tomography data assigned to the blood vessel segment or at least one value derived therefrom. Adjacent hollow organ segments of the hollow organ are defined based on supply by adjacent blood vessels in the tree structure, and the tree structure and the perfusion information are analyzed to determine hemodynamic information to assign to hollow organ segments. At least a part of the hemodynamic information in at least one of the computed tomography dataset or a visualization dataset derived therefrom is then visualized.

A setting reception unit obtains information identifying an object selected by a user from foreground objects as a target to be a part of the background. A backgrounded target determination unit identifies the model ID of the selected object based on the object identifying information obtained and three-dimensional shape data. Based on the three-dimensional shape data, the determination unit identifies a foreground ID corresponding to the identified model ID, in a captured image from an actual camera. The determination unit obtains coordinate information and mask information in foreground data corresponding to the foreground ID identified, generates a correction foreground mask, and sends the mask to a background correction unit in an image processing unit. The background correction unit generates a correction image by masking the captured image using the mask, superimposes the correction image onto the background image, and outputs it as a corrected background image.

The present invention relates to a medical data processing method of determining the representation of an anatomical body part (2) of a patient (1) in a sequence of medical images, the anatomical body part (2) being subject to a vital movement of the patient (1), the method being constituted to be executed by a computer and comprising the following steps: a) acquiring advance medical image data comprising a time-related advance medical image comprising a representation of the anatomical body part (2) in a specific movement phase; b) acquiring current medical image data describing a sequence of current medical images, wherein the sequence comprises a specific current medical image comprising a representation of the anatomical body part (2) in the specific movement phase, and a tracking current medical image which is different from the specific current medical image and comprises a representation of the anatomical body part (2) in a tracking movement phase which is different from the specific movement phase; c) determining, based on the advance medical image data and the current medical image data, specific image subset data describing a specific image subset of the specific current medical image, the specific image subset comprising the representation of the anatomical body part (2); d) determining, based on the current medical image data and the image subset data, subset tracking data describing a tracked image subset in the tracking current medical image, the tracked image subset comprising the representation of the anatomical body part (2).

The invention provides a method for generating a training set of data for training a classifier relating to a physiological condition. The method begins by obtaining a first set of data relating to a first plurality of subjects and a second set of data relating to a second plurality of subjects, wherein each of the first set of data and the second set of data are grouped into a plurality of subsets of data, wherein the plurality of subsets of data is associated with a plurality of features. Descriptive statistics are calculated for each of the plurality of subsets of data within the first set of data and one or more features within the plurality of features is selected based on the calculated descriptive statistics to generate a search criterion. A supplementary set of data is identified from the second set of data by applying the search criterion to the second set of data. The training data set is then compiled based on the first set of data and the supplementary set of data.p

Provided is an image sensor including a pixel array formed by arranging pixels, which generate an electrical signal in response to light; a memory for storing a register value of the image sensor; and a sensor controller for configuring the register value, wherein the register value includes information for defining a region to be processed in the pixel array, and when a change request for changing at least one of a position and a size of the region to be processed is received, the sensor controller provides a register modification command for adjusting the register value so as to correspond to the change request to the image sensor or the memory.

A feature region tracking process method includes temporarily stopping the output of camera images being successively acquired; accumulating, as accumulated image data, respective camera images that are successively acquired after the time of temporal stoppage, starting from the time of temporal stoppage; accepting position designation in a camera image being output at the time of temporal stoppage; and, when the position designation has been accepted, performing a tracking process in sequence on a feature region in the camera images included in the accumulated image data from the camera image acquired at the time of temporal stoppage to the latest camera image, using the designated position as the feature region.

The usability in annotating an image of a subject derived from a living body is improved. An image analysis method is implemented by one or more computers and includes: displaying a first image that is an image of a subject derived from a living body; acquiring information regarding a first region based on a first annotation added to the first image by a user (S101); specifying a similar region similar to the first region from a region different from the first region in the first image, or a second image obtained by image capture of a region including at least a part of a region of the subject subjected to capture of the first image, based on the information regarding the first region (S102, S103); and displaying a second annotation in a second region corresponding to the similar region in the first image (S104).

A method for inspecting an object includes determining guide image data of the object from a determined orientation, the guide image data including a guide image pixel array and a pixel property for at least one guide image pixel in the guide image pixel array. The method also includes receiving inspection image data indicative of an inspection image and associating the inspection image data with the guide image data with a processor of a computing device. Additionally, the method includes determining a property of the object based on the guide image data and the associated inspection image data.