A method and system are provided to intraoperatively adjust the dimensions of a pre-operatively planned implant cavity to improve implant fit in a bone. The method includes obtaining a preoperative image data set of the bone. A surgical plan is generated using the image data set and/or a three-dimensional (3-D) bone model of the patient's bone generated from the image data set. Intraoperatively, the patient's bone is exposed and registered to the surgical plan and a computer assisted surgical system. The computer assisted surgical system having a cutting tip and a force sensor for sensing actual forces exerted on the cutting tip as an initial cut is created on the bone at a first bone region. Based on the difference between the actual cutting force and the expected cutting force in the plan, the dimensions of the cavity are adjusted accordingly.

A health care assisting device includes: an image acquisition part that acquires a plurality of images in which a target person is photographed in time series; an expression recognizer that recognizes a feature of an expression of the target person from the plurality of images acquired by the image acquisition part; a storage in which expression recognition results of the plural images are stores as time-series data; a health state estimator that detects a feature associated with a temporal change of the expression of the target person from the time-series data stored in the storage, and estimates a mental health state of the target person based on the detected feature; and an output part that outputs information on the mental health state of the target person based on an estimation result of the health state estimator.

A method is disclosed for spinal anatomy segmentation. In one example, the method includes combining a fully convolutional network with a residual neural network. The method also includes training the combined fully convolutional network with the residual neural network from end to end. The method also includes receiving at least one medical image of a spinal anatomy. The method also includes applying the fully convolutional network with the residual neural network to at least one medical image and segmenting at least one vertebral body from the at least one medical image of the spinal anatomy.

The invention is directed to an apparatus for finding a functional tissue area in a tissue region. The apparatus has a measurement illuminating device suitable for emitting measurement illumination to the tissue region and a camera which can capture light reflected by the tissue region. The camera has a green channel and/or a blue channel wherein there is a change in an optical property of the light reflected by the tissue region during the stimulation thereof which is undertaken at least intermittently. An evaluation unit captures the change in the optical property only by a signal of the green channel and/or of the blue channel of the camera. A display unit can display an output signal of the evaluation unit for the functional tissue area in the tissue region.

Some aspects of the present disclosure relate to ultrashort-echo-time (UTE) imaging. In one embodiment, a method includes acquiring UTE imaging data associated with an area of interest of a subject. The acquiring comprises applying an imaging pulse sequence with a three-dimensional (3D) spiral acquisition and a nonselective excitation pulse. The method also includes reconstructing at least one image of the area of interest from the acquired UTE imaging data.

A plurality of stimulations is transmitted to tissue or other material using one or more transmitters. The plurality of signals associated with the excited tissue and the transmitted stimulations are measured. The measured signals are processed to generate field-related quantities, such as B1+ and/or MR signal maps. Field-related quantities are generated also from simulation, by calculating the one or more incident fields from a simulator model of the one or more transmitters and assuming a given distribution of electrical properties in the tissue or other material. Field-related quantities generated from simulation and experimental procedures are compared to each other. The assumed electrical properties distribution is updated and the procedure is repeated iteratively until the difference between simulated and experimental field-related quantities is smaller than a threshold.

This document describes automated abdominojugular reflux (AJR) testing. To automate AJR tests, a pressure cuff wrapped around a person's abdomen applies pressure while video of their neck is captured. By way of example, a medical professional wraps a pressure cuff around the person's abdomen and records video of the person's neck using a smartphone, which communicates with the pressure cuff to synchronize the application of pressure with video capture. The video is processed to detect and track the response of jugular venous pulse (JVP), which is compared to AJR test thresholds to determine test results. While determining JVP, and thereby results of AJR tests, from reconstructed videos may not result in data that is as accurate as invasive intra-heart tests, it requires little if any risk to patients and is easy for medical professionals to perform. Further, these techniques enable AJR tests to be performed automatically and without relying on estimates made by skilled medical professionals.

An apparatus includes a communication interface and at least one processor. The processor is configured to obtain a size of a lumen in each of a plurality of aortic zones and first information for each of the plurality of aortic zones based on segmentation results of an aorta and the plurality of aortic zones within the aorta; and visualize the size of the true lumen, the first information, and a ratio between the size of the true lumen and the first information in each of the plurality of aortic zones by using a visualization segment corresponding to each of the plurality of aortic zones.

A computer-implemented method of visualizing blood flow through a patient using magnetic resonance imaging (MRI) includes receiving an image of the portal venous system of the patient's liver at a full field of view. A reduced field of view is defined which encompasses the portal venous system of the patient's liver and excludes extraneous anatomy in the full field of view. A navigator area is defined in the full field of view and outside of the reduced field of view. Transmit channels are used to selectively excite the reduced field of view and the navigator area throughout a cardiac cycle of the patient. Measurement data is acquired in response to the selective excitation. The acquired data is used to generate time-resolved 3D datasets. Additionally, a 3D visualization of blood flow though the portal venous system is generated based on the time-resolved 3D datasets.

A camera assembly for use in medical tracking applications having a range camera and a thermographic camera in a fixed relative position. The range camera is configured to acquire a first image of an object at a first instant of time and a second image at a second instant of time. The thermographic camera is configured to acquire a first thermal image of the object at the first instant and a second thermal image at the second instant. A processor identifies at least one point pair in the first thermal image and the second thermal image. The at least one point pair is mapped to corresponding point pairs associated with the first image and the second image. Movement of the object is determined based on the mapping.