Provided is a 3D bone density and bone age calculation apparatus using an artificial intelligence-based rotation manner. The 3D bone density and bone age calculation apparatus includes a main body, and the main body includes a rotary drum including a drum shaft gear, an X-ray generator, an intensifying screen, and an image data capturer, a drum driver including a motor shaft gear connected to the drum shaft gear so as to rotate the rotary drum, a motor, support rollers and one of an origin sensor and an encoder, an outer case and an inner case, a front case and a rear case, a capturing holder, and a controller configured to select an image-captured position of the rotary drum, and configured to input a current age, sex and nutritional status of a patient, etc. The controller includes a display configured to display captured images and a diagram indicating bone age.

A medical scan assisted review system is operable to receive, via a network, a medical scan for review. Abnormality data is generated by identifying a plurality of abnormalities in the medical scan by utilizing a computer vision model that is trained on a plurality of training medical scans. The abnormality data includes location data and classification data for each of the plurality of abnormalities. Text describing each of the plurality of abnormalities is generated based on the abnormality data. The abnormality data and the text is transmitted to a client device. A display device associated with the client device displays the abnormality data in conjunction with the medical scan via an interactive interface, and the display device further displays the text via the interactive interface.

A method of establishing a quantitative measure of contrast enhancement in contrast medical imaging through computer analysis of baseline and enhanced images allows statistical comparison of protocols and imaging parameters from routine hospital operations to enhance and evaluate such protocols and parameters.

A prediction device includes a first prediction unit that outputs first prediction information regarding a joint at a second point in time after a predetermined period of time from a first point in time, from a medical image showing the joint of a subject at the first point in time. The first prediction unit includes a first prediction model capable of estimating the first prediction information from the medical image.

Patient misidentification errors in medical imaging can result in serious consequences, such as the misdiagnosis of a disease state or the application of an inappropriate treatment regimen. Systems, methods, and apparatuses disclosed herein can properly and consistently identify, adjust, and/or correlate radiologic images with the correct patient. Systems and methods for automated and robust image capture are also provided. Methods for identifying a disease state in a patient and/or for treating a patient having the identified disease state are disclosed and can be based on characteristics identified through deep learning convolutional neural networks and that are associated with photographic and radiologic patient images.

A display control unit displays, on a display unit, at least some of a plurality of images included in each of a plurality of image sets of the same object which have been captured at different imaging dates and times and each of which consists of the plurality of images including at least a plurality of tomographic images acquired by performing tomosynthesis imaging for the object. A setting unit sets at least one past image set, which was acquired at an imaging date and time before the latest imaging date and time and includes images at least some of which have been displayed, among the plurality of image sets as having been displayed.

An X-ray source transmits X-rays through a subject and a detector receives the X-ray energy after having passed through the subject. A processing system generates a pre-shot image of the subject using low energy X-ray intensity from the X-ray source and determines a plurality of acquisition parameters for a main scan of the subject based on the pre-shot image. A saturation time of the detector for the corresponding acquisition parameters is determined based on detector calibration data and to determine a number of time frames required to reach the targeted dose based on the saturation time. An X-ray dosage level of the subject is then applied using the X-ray source based on the number of time frames and to generate the image of the subject based on the detected X-ray energy at the X-ray detector for the applied X-ray dosage level.

An electronic device includes a processor configured to generate a position movement prediction field indicating prediction of a potential positional change of a branch path by a patient's biological activity for one or more branch paths based on a blood vessel image of a reference frame, correct guidewire information extracted from a blood vessel image of a target frame with respect to a catheter position of the reference frame, and select a branch path to dispose the guidewire information, among one or more branch paths of a blood vessel region based on the position movement prediction field and the corrected guidewire information; and a display configured to visualize the guidewire information on the selected branch path.

Systems, methods and instrumentalities are described herein for automating a medical environment. The automation may be realized using one or more sensing devices and at least one processing device. The sensing devices may be configured to capture images of the medical environment and provide the images to the processing device. The processing device may determine characteristics of the medical environment based on the images and automate one or more aspects of the operations in the medical environment. These characteristics may include, e.g., people and/or objects present in the images and respective locations of the people and/or objects in the medical environment. The operations that may be automated may include, e.g., maneuvering and/or positioning a medical device based on the location of a patient, determining and/or adjusting the parameters of a medical device, managing a workflow, providing instructions and/or alerts to a patient or a physician, etc.

An X-ray diagnosis apparatus comprises processing circuitry. The processing circuitry is configured: to generate first subtraction image by using a first image acquisition condition; to generate second subtraction image by using a second image acquisition condition that are substantially same as the first image acquisition condition; to generate first color image by using a first processing condition, each pixel of the first color image having a color according to a temporal transition at a corresponding position of the first subtraction image; to generate, by using a second processing condition that is substantially same as the first processing condition, second color image, each pixel of the second color image having a color according to a temporal transition at a corresponding position of the second subtraction image; and to cause a stereoscopic image to be displayed on the basis of the first color image and the second color image.