An image analysis apparatus includes: an image input section; a region extraction section configured to set an analysis object region for each of a first image and a second image acquired after the first image, the first image and the second image being inputted from the image input section; and an image analysis section configured to calculate a brightness decrease degree of a part of the analysis object region in the second image, the part having a brightness decreased relative to the analysis object region in the first image.

Sonography systems and methods for performing sonography are provided in which the gender of a fetus is obfuscated. Gender is obfuscated by blurring or otherwise obfuscating the genitalia of the fetus in a sonogram, optionally also by subtly modifying features like dimensions of bones from which gender could otherwise by deduced, and by modifying sonography data so that if copied and removed from the sonography system the gender of the fetus is obfuscated in the copy. Trained neural networks are employed to locate genitalia and to correctly identify gender from features other than the genitalia so that the genitalia can be obfuscated and other features subtly modified to evade gender detection.

An imaging system and method for microbial growth detection, counting or identification. One colony may be contrasted in an image that is not optimal for another type of colony. The system and method provides contrast from all available material through space (spatial differences), time (differences appearing over time for a given capture condition) and color space transformation using image input information over time to assess whether microbial growth has occurred for a given sample.

A location identification system analyzes information received corresponding to a device detected in a room of a patient. On detecting a location identification of the device, the system assigns the device to the location corresponding to the location identification. In embodiments, the system retrieves patient and care team information for the location. The location and patient and care team information may be communicated to a central video monitoring system.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for classifying a patient. In one aspect, a method comprises: receiving multi-modal data characterizing a patient, wherein the multi-modal data comprises a respective feature representation for each of a plurality of modalities; processing the multi-modal data characterizing the patient using an encoder neural network to generate an embedding of the multi-modal data characterizing the patient; determining a respective classification score for each patient category in a set of patient categories based on the embedding of the multi-modal data characterizing the patient; and classifying the patient as being included in a corresponding patient category from the set of patient categories based on the classification scores.

A method for studying the behavior of an animal in an experimental area including stimulating the animal using a stimulus device; collecting data from the animal using a data collection device; analyzing the collected data; and developing a quantitative behavioral primitive from the analyzed data. A system for studying the behavior of an animal in an experimental area including a stimulus device for stimulating the animal; a data collection device for collecting data from the animal; a device for analyzing the collected data; and a device for developing a quantitative behavioral primitive from the analyzed data. A computer implemented method, a computer system and a nontransitory computer readable storage medium related to the same. Also, a method and apparatus for automatically discovering, characterizing and classifying the behavior of an animal in an experimental area. Further, use of a depth camera and/or a touch sensitive device related to the same.

Systems and methods for producing ultrasound images are disclosed herein. In one embodiment, ultrasound image data are acquired in discrete time increments at one or more positions relative to a subject. Control points are added by a user for two or more image frames and a processor interpolates the location of the control points for image frames obtained at in-between times.

The invention relates to systems and methods to assist physicians in decision making for stroke patients. In particular the systems and methods can be used to assist physicians to decide on whether a patient with an acute ischemic stroke has a large vessel occlusion (LVO) and should be transferred from a community hospital to a larger hospital to undergo an endovascular thrombectomy procedure.

A learning system which is capable of easily collecting data of affected parts having completely recovered, as training data. When it is determined that an affected part has completely recovered based on affected-part image data generated by shooting the affected part, image data accompanied with the same affected part ID as that of the affected-part image data is identified from among image data set stored in a storage device of the learning system. The actual number of days to a complete recovery of the affected part is calculated from shooting dates of the identified image data and the affected-part image data, and is added to the affected-part image data. The affected-part image data accompanied with the actual number of days to the complete recovery is used as training data to create a trained model that predicts the number of days to a complete recovery of the affected part.

An image processing apparatus obtains segment definition information that defines a plurality of segments obtained by dividing a human body along a body axis, and obtains a three-dimensional image including a plurality of slice images indicating cross sections of a subject. The image processing apparatus identifies, based on the segment definition information, a segment to which a cross section corresponding to at least one slice image among the slice images included in the image belongs, and calculates a coordinate value of the at least one slice image, based on the identified segment and a reference coordinate system in which a coordinate value is defined for each of the segments.