It is an object of the present invention to provide an object collating device and an object collating method that enable matching of images of a dividable medical article with desirable accuracy and easy confirmation of matching results. In the object collating device according to the first aspect, when the object is determined to be divided, the first image for matching is collated with the image for matching (the second matching image) for the objects in the undivided state, so that the region to be matched is not narrowed, and matching of the images of the dividable medical article is achieved with desirable accuracy. In addition, since the first and second display processing is performed on the images for display determined to contain the objects of the same type, matching results can easily be confirmed.

Various methods and systems are provided for identifying future occurrences of lesions in a patient. In one example, a method includes feeding first images collected from one or more patients prior to appearance of lesions and second images collected from the one or more patients after appearance of the lesions to a processor to train a model to predict a location of a future lesion. The method further includes inputting third images collected from a new patient to the processor to infer regions for future lesions, and displaying the inferred regions in a probability map at a display unit to indicate areas of increased likelihood of lesion occurrence.

An object of the present disclosure is to provide a technique capable of acquiring an analysis target region and color information without causing a decrease in extraction accuracy of the analysis target region due to erroneous extraction of a color of a colored label, measuring a solution volume of the specimen, and determining a specimen type. The biological specimen analysis device according to the present disclosure creates a developed view by cutting out a partial region from a color image of a biological sample tube and connecting the partial region along a circumferential direction of the biological sample tube, and extracts a detection target region from the developed view (see FIG. 6B).

A shape identification program causes a computer to execute a process including: acquiring a third shape dataset and a fourth shape dataset, respectively generated by changing sizes of a first shape dataset and a second shape dataset in each of directions of a plurality of coordinate axes according to a specific rule; and generating a first plurality of images and a second plurality of images by capturing the third shape dataset and the fourth shape dataset, respectively, from both directions of the respective plurality of coordinate axes. The process further includes identifying a second portion in the second shape dataset corresponding to a first portion in the first shape dataset by aligning orientations of the first shape dataset and the second shape dataset based on a result of comparison between the first plurality of images and the second plurality of images.

A hologram detection method according to an aspect of the disclosure, includes: inputting a first image, obtained by capturing a detection object on the basis of first flash intensity, to a neural network model to obtain a first detection result value representing the detection or not of a hologram for each of predetermined at least one detection unit regions; and comparing a threshold value with the first detection result value obtained for each detection unit region to determine the detection or not of a hologram in the first image and a first detection unit region where a hologram is detected.

An information processing apparatus includes a processor configured to: acquire information indicating a size of an external shape of each of characters in data of a first image and data of a second image that are used for comparison; and determine a presence or absence of a fault in the data of the second image with respect to each of the characters with reference to a degree of a difference that is between the data of the second image and the data of the second image and is detected in accordance with a detection condition varying in response to the size of the external shape of each of the characters.

A wearable device for use in immersive reality applications is provided. The wearable device includes eyepieces to provide a forward-image to a user, a first forward-looking camera mounted on the frame and having a field of view, a processor configured to identify a region of interest within the forward-image, and an interface device to indicate to the user that a field of view of the first forward-looking camera is misaligned with the region of interest. Methods of use of the device, a memory storing instructions and a processor to execute the instructions to cause the device to perform the methods of use, are also provided.

A method is provided herein that discloses receiving, by a processor, first image data comprising first bioluminescence data derived from an organism at a first time, receiving, by the processor, second image data comprising second bioluminescence data derived from an organism at a second time, comparing, by the processor, the first image data to the second image data, determining, by the processor, whether a peak light output event has occurred based on the comparison, and outputting, by the processor and to a display device, an indication that the peak light output event has occurred.

An object detection device that detects a specific object included in an input image includes a first candidate region specifying unit that specifies a first candidate region in which an object candidate is included from a first input image obtained by imaging a subject in a first posture, a second candidate region specifying unit that specifies a second candidate region in which an object candidate is included from a second input image obtained by imaging the subject in a second posture different from the first posture, a deformation displacement field generation unit that generates a deformation displacement field between the first input image and the second input image, a coordinate transformation unit that transforms a coordinate of the second candidate region to a coordinate of the first posture based on the deformation displacement field, an association unit that associates the first candidate region with the transformed second candidate region that is close to the first candidate region, and a same object determination unit that determines that the object candidates included in the candidate regions associated with each other by the association unit are the same object and are the specific object.

An airport approach assistance system for aircraft includes a controller including electronic circuitry configured to: obtain a first image captured by a camera configured to capture images of a field of view ahead of the aircraft; obtain a second image stored in a database representing a runway where the aircraft is supposed to land; make changes to the first image and/or to the second image, in order to transpose them into a same spatial reference frame; extract a first region of interest from the first image, so as to isolate a landing area; compare the extracted first region of interest with a second region of interest associated with the second image; and generate a signal according to a comparison result. Thus, a pilot of the aircraft is assisted in confirming that the landing takes place on the expected landing runway.