For partial volume correction, the partial volume effect is simulated using patient-specific segmentation. An organ or other object of the patient is segmented using anatomical imaging. For simulation, the locations of the patient-specific object or objects are sub-divided, creating artificial boundaries in the object. A test activity is assigned to each sub-division and forward projected. The difference of the forward projected activity to the test activity provides a location-by-location partial volume correction map. This correction map is used in reconstruction from the measured emissions, resulting in more accurate activity estimation with less partial volume effect.

A network is machine trained to estimate flow by spatial location based on input of anatomy information. A medical scan of tissue may be used to generate flow information without the delay or difficulty of performing a medical scan configured for flow imaging or CFD. Anatomy imaging is used to provide flow estimates with the speed provided by the machine-learned network.

The present disclosure discusses systems and methods for identifying biomarkers that can help with the diagnosis, prognosis, and treatment choices of patients with neurodegenerative diseases. Diffusion based magnetic resonance imaging can often fail for patients with a neurodegenerative disease because parameters fractional anisotropy, mean diffusivity, and radial diffusivity are based on simple models that can fail in the presence of neurodegeneration, such as demyelination. The present disclosure discusses systems and methods that enhance dMRI images and enable tractography to be performed on images of a damaged nervous system. The damaged tracks identified by the present system can be used as a biomarker for the assessment of patients. In some implementations, the biomarkers are converted into clinical scales that can be used to compare patients to one another or over time.

A method is disclosed for graphically depicting a marker which is applied to an examination object in an imaging system. In an embodiment, the position of the marker is ascertained by way of a first measuring method. An image of the examination object is provided on the basis of a second measuring method, in which image the position of a graphical object that represents the marker in the image is ascertained and depicted on the basis of the first measuring method.

For partial volume correction, the partial volume effect is simulated using patient-specific segmentation. An organ or other object of the patient is segmented using anatomical imaging. For simulation, the locations of the patient-specific object or objects are sub-divided, creating artificial boundaries in the object. A test activity is assigned to each sub-division and forward projected. The difference of the forward projected activity to the test activity provides a location-by-location partial volume correction map. This correction map is used in reconstruction from the measured emissions, resulting in more accurate activity estimation with less partial volume effect.

Methods for performing digital subtraction angiography of a region of interest of a patient are described herein. The methods include acquiring a filled image data set of the region of interest by x-ray imaging and creating an angiography image data set by subtracting a mask image data set from the filled image data set, wherein an x-ray imaging device for x-ray imaging and a further imaging device for at least one additional imaging modality are co-registered and operable to acquire image data in the same field of view, wherein the imaging devices are used to simultaneously acquire the filled image data set using the x-ray imaging device and an anatomy data set using the further imaging device and the mask image data set in derived from the anatomy data set in a conversion process, which converts additional imaging modality image data into virtual x-ray image data.

An image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires a magnetic resonance (MR) image in which objects of interest scattered in a brain of a subject are rendered. The processing circuitry acquires connection information indicating connectivity among a plurality of regions of the brain. The processing circuitry performs an analysis with use of the MR image and the connection information, and calculates analytical values related to the objects of interest and allocated to the regions.

A method for analyzing performance of an imaging device including a scanner with a phantom includes receiving image data related to a scanning, by the scanner, of a first part of the phantom including at least part of a first test component. The method also includes obtaining at least one positioning parameter indicative of a positioning manner of the phantom during the scanning. The method further includes generating a first test image based on the received image data and determining a first region of interest (ROI) related to the first test component in the first test image based on the at least one positioning parameter.

There is provided a method for segmentation of an image of a target patient, comprising: providing a target 2D slice and nearest neighbor 2D slice(s) of a 3D anatomical image, and computing, by a trained multi-slice fully convolutional neural network (multi-slice FCN), a segmentation region including a defined intra-body anatomical feature that extends spatially across the target 2D slice and the nearest neighbor 2D slice(s), wherein the target 2D slice and each of the nearest neighbor 2D slice(s) are processed by a corresponding contracting component of sequential contracting components of the multi-slice FCN according to the order of the target 2D slice and the nearest neighbor 2D slice(s) based on the sequence of 2D slices extracted from the 3D anatomical image, wherein outputs of the sequential contracting components are combined and processed by a single expanding component that outputs a segmentation mask for the target 2D slice.

A method of medical image registration with respect to a volume of interest (VOI) and an apparatus for performing the method are provided. In one embodiment, the method includes obtaining a first medical image of a selected section of the VOI, from a first medical apparatus, detecting a sectional image corresponding to the selected section from second medical images previously captured of the VOI, based on an anatomical feature appearing in the first medical image, mapping virtual coordinate schemes of the first and second medical images to produce a mapped virtual coordinate scheme, based on the detected sectional image and the first medical image, and tracking a movement of a section of the VOI captured by the first medical apparatus in the second medical images by using a mapped virtual coordinate scheme.