By subjecting a neural network to machine learning using teacher data consisting of learning data and correct answer data, a trained neural network that outputs at least one of a composition of a target subject or a body thickness of the target subject in a case in which at least one target radiation image of the target subject is input is constructed. The learning data includes a standard image acquired by irradiating a standard object of which a thickness and a material are known with radiation in a state in which an object is interposed between the standard object and a radiation detector, an energy characteristic of the radiation, a thickness and a material of the object, and an imaging condition in a case in which the standard image is acquired. The correct answer data includes at least one of a composition or a body thickness of a subject derived from at least one radiation image of the subject by using the standard image, the energy characteristic of the radiation, the thickness and the material of the object, and the imaging condition.

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.

A bone information acquisition apparatus comprises: an X-ray image acquisition unit configured to acquire an X-ray image with a subject; an identifying unit configured to identify a mounted state of a grid that removes scattered rays; and a bone information acquisition unit configured to acquire bone information that evaluates a state of a bone of the subject included in the X-ray image in accordance with the mounted state of the grid.

The present invention relates to a method to improve quality control (QC) accuracy. The method comprises at least one input quality control (IQC) check and at least one output quality control (OQC) check for the image to be analyzed. The integrated IQC and OQC results may be mapped onto a pre-defined multi-dimensional space to evaluate the overall QC result.

Teeth are screened for periodontal disease using digitized images manipulated and annotated on a processor. A digitized radiographic image of a tooth shows locations of a bone boundary and a cemento-enamel junction (CEJ) of the tooth. The digitized radiographic image is marked on the processor with a location on the bone boundary and with a pair of CEJ points at opposite ends of the CEJ visible in the radiograph. A ratio between (a) a distance between the bone boundary location and the adjacent CEJ point as numerator and (b) a distance between the CEJ points as denominator is calculated on the processor and compared with a threshold ratio-value for a corresponding tooth from a database accessible by the processor. A calculated ratio-value which is greater than the database threshold ratio-value is indicative of periodontal disease in the tooth. The probability of the correct diagnostic decision is determined by the relative magnitude of the calculated ratio-value and the threshold ratio-value.

Various methods and systems are provided for automatically or semi-automatically adjusting one or more ultrasound imaging parameters for imaging in a second mode based on images obtained in a first mode. In one example, a method includes operating an ultrasound imaging system in a first operating mode, determining an anatomy imaged by the ultrasound imaging system in the first operating mode, and responsive to an operating mode transition request, adjusting imaging parameters of the ultrasound imaging system in a second operating mode based on the first operating mode and the anatomy imaged in the first operating mode.

Spinal correction surgical techniques and methodologies for correction of scoliosis using non fusion anterior scoliosis correction, including soft tissue releases, unique correction techniques such as de-rotation, and unique single and dual anchor screw/cord applications.

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.

The present disclosure provides a system and method for image data acquisition. The method may include obtaining image data of a subject including a first type of tissue and a second type of tissue. The method may include determining, based on the image data of the subject, a target portion including at least a portion of at least one of the first type of tissue or the second type of tissue. The method may include determining, based at least in part on the target portion represented in the image data, a scan mode corresponding to the target portion. The method may include causing an imaging device to acquire, based on the scan mode, image data of the target portion.

This disclosure relates to an intraoperative guidance system for total joint replacement of a joint of a patient by a surgeon. The guidance system comprises: an X-ray imaging device for single-shot application of X-ray radiation to the joint and for etecting X-ray radiation to create a digital image of the joint and an implant component during a total joint replacement surgery; and a computer system configured to: store a digital three-dimensional model of the joint; receive the digital image during the total joint replacement surgery; perform registration between the digital image and the digital three-dimensional model to determine a placement of the implant component in the digital image in relation to the digital three-dimensional model; determine an intraoperative simulated erformance metric and provide an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component.