A method may include identifying a simulated three-dimensional representation corresponding to an internal anatomy of a subject based on a match between a computed two-dimensional image corresponding to the simulated three-dimensional representation and a two-dimensional image depicting the internal anatomy of the subject. Simulations of the electrical activities measured by a recording device with standard lead placement and nonstandard lead placement may be computed based on the simulated three-dimensional representation. A clinical electrogram and/or a clinical vectorgram for the subject may be corrected based on a difference between the simulations of electrical activities to account for deviations arising from patient-specific lead placement as well as variations in subject anatomy and pathophysiology.

Provided is an observation device including: a stereo image-acquisition optical system that acquires images of cells floating in a culture fluid inside a culture vessel; and an analyzer that calculates a cell density of the cells on the basis of the images acquired by the stereo image-acquisition optical system, wherein the analyzer identifies a three-dimensional position of each of the cells included in the images and calculates the cell density on the basis of the number of cells present within a predetermined three-dimensional region.

An apparatus includes a sensor configured to capture an image of an affected part, and a processor configured to obtain information about a size of the affected part in the captured image, and control timing to capture an image of the affected part or control timing to prompt a user to perform an imaging operation based on the information about the size of the affected part.

Aneurysms are classified and quantitatively analyzed based on medical image data acquired from a subject. In general, one or more algorithms are implemented to automatically classify, or otherwise diagnose, and measure aneurysms and their change over time. These algorithms make use of artificial intelligence and deep learning to develop quantitative analytics that can be consolidated into diagnostic reports.

There are provided a medical image processing device, and endoscope system, a diagnosis support method, and a program which can support diagnosis by avoiding an inappropriate report in a case where any of site information of an observation target and lesion type information detected from a medical image is incorrect. The medical image processing device includes at least one processor. The at least one processor acquires the medical image, acquires the site information indicating a site of an observation target included in the medical image, in a human body, detects a lesion from the medical image to acquire the lesion type information indicating a lesion type, determines presence or absence of a contradiction between the site information and the lesion type information, and decides a report mode of the site information and the lesion type information on the basis of a determination result.

A method for determining one or more vital signs of a person includes recording video images of a scene with an egocentric camera coupled to the person's body, detecting and magnifying image frame-to-image frame movements in the video images of the scene, representing the magnified image frame-to-image frame movements in the video images of the scene by a one-dimensional (1D) amplitude-versus-time series, and transforming the 1D amplitude-versus-time series representation into a frequency spectrum. The method further includes identifying one or more local frequency maxima in the frequency spectrum as corresponding to one or more vital signs of the person.

A method for predicting the morphological changes of liver tumor after ablation based on deep learning includes: obtaining a medical image of liver tumor before ablation and a medical image of liver tumor after ablation; preprocessing the medical image of liver tumor before ablation and the medical image of liver tumor after ablation; obtaining a preoperative liver region map, postoperative liver region map, and postoperative liver tumor residual image map; obtaining a transformation matrix by a Coherent Point Drift (CPD) algorithm and obtaining a registration result map according to the transformation matrix; training the network by a random gradient descent method to obtain a liver tumor prediction model; using the liver tumor prediction model to predict the morphological changes of liver tumor after ablation. The method provides the basis for quantitatively evaluating whether the ablation area completely covers the tumor and facilitates the postoperative treatment plan for the patient.

There is provided a microparticle composition suitable for molecular imaging, the composition comprising microparticles, wherein the microparticles comprise: a core microparticle structure having a central area and a shell, and wherein the core microparticle structure comprises (i) a phosphatidylcholine lipid: (ii) a phosphatidylethanolamine lipid comprising at least one maleimide moiety; and (iii) an alkoxylated fatty acid.

A method and system is for assisting a user in positioning an ultrasound probe relative to a subject's body. In use, the user moves the probe through a series of positions, and ultrasound image data is captured for each position, the data at each position corresponding to a particular imaging view of the anatomical region being imaged. An assessment procedure (16) is operable to process ultrasound data for different imaging views, and to determine for the data for each view a rating, representative of the suitability of the data for that view for observing one or more anatomical features or deriving one or more clinical parameters from the data. Guidance feedback is generated (18) for the user for assisting the user in positioning the probe, wherein the guidance feedback is based on a history (26) of image view quality over time over the course of the imaging procedure. For example, a trend in image view quality over time may be determined and output to a user, from which the user can quickly tell whether they are moving toward (in the case of increasing quality) or away from (decreasing quality) an optimum imaging position.

An output device performs: acquiring a plurality of images chronologically captured by a camera located to photograph an inside of a bowl of a toilet; extracting, from the acquired images, an excrement image showing excrement; extracting, from the acquired images, a blood image showing a blood spot; determining, based on time information about the excrement image, an excretion start time; determining, based on time information about the blood image, a blood appearance start time, and determining, based on the blood image, a blood size indicating a size of the blood spot; generating, as excretion information, information including the excretion start time, the blood appearance start time, and the blood size; and outputting the generated excretion information.