The present invention relates to image processing devices and related methods. The image processing device (10) comprises a data input (11) for receiving spectral computed tomography volumetric image data organized in voxels. The image data comprises a contrast-enhanced volumetric image of a cardiac region in a subject's body and a baseline volumetric image of that cardiac region, e.g. a virtual non-contrast image, wherein the contrast-enhanced volumetric image conveys anatomical information regarding coronary artery anatomy of the subject. The device comprises a flow simulator (12) for generating, or receiving as input, a three-dimensional coronary tree model based on the volumetric image data and for simulating a coronary flow based on the three-dimensional coronary tree model. The device comprises a perfusion synthesis unit (13) for generating a perfusion image representative of a blood distribution in tissue at at least one instant in time taking at least the baseline volumetric image and said coronary flow simulation into account.

A framework for sensor-based patient treatment support. In accordance with one aspect, one or more sensors are used to acquire sensor data of one or more objects of interest. The sensor data is then automatically interpreted to generate processing results. One or more actions may be triggered based on the processing results to support treatment of a patient, including supporting medical scanning of the patient.

A computer-implemented method for personalized assessment of patients with acute coronary syndrome (ACS) includes extracting (i) patient-specific coronary geometry data from one or more medical images of a patient; (ii) a plurality of features of a patient-specific coronary arterial tree based on the patient-specific coronary geometry data; and (iii) a plurality of ACS-related features from additional patient measurement data. A surrogate model is used to predict patient-specific hemodynamic measures of interest related to ACS based on the plurality of features of the patient-specific coronary arterial tree and the plurality of ACS-related features from the additional patient measurement data.

An imaging apparatus and associated methods are provided to efficiently estimate scatter during multi-fraction treatments for improved quality and workflow. Estimated scatter from one fraction during a treatment course can be utilized during subsequent fractions, allowing for measurements with higher scatter-to-primary ratios. The quality of scatter estimates can be maintained, while workflow improves and dosage decreases. Scan configuration limits can be utilized to maintain a minimum level of scatter measurement quality. Patient information can be monitored to ensure that prior fraction scatter estimates are still applicable to current patient status.

A method and apparatus for vascular assessment are disclosed. The apparatus, in some embodiments, receives a plurality of 2-D angiographic images of a portion of a vasculature of a subject, and processes the images to produce a stenotic model over the vasculature. The stenotic model has measurements of the vasculature at one or more locations along vessels of the vasculature. The apparatus, in some embodiments, determines a flow characteristic of the stenotic model and calculates an index indicative of vascular function, based, at least in part, on the flow characteristic in the stenotic model.

For a particularly comprehensive identification of hollow organ systems, a method is provided for producing a digital subtraction angiography of a hollow organ system of a patient. The method includes: providing mask image data recorded by an X-ray device; providing at least first fill image data recorded by the X-ray device, which has been recorded during an at least partial filling of the hollow organ system with a contrast agent; starting from a first intravenous and a second intraarterial contrast agent injection following in time; ascertaining at least first subtraction image data by subtracting the mask image data from the at least first fill image data; ascertaining final subtraction image data from the at least first subtraction image data; and segmenting the final subtraction image data and assigning the pixels or voxels of the final subtraction image data to at least two different intensity classes based on their respective intensity value.

A method for evaluating image quality is provided. The method may include: obtaining an image, the image including a plurality of elements, each element of the plurality of elements being a pixel or voxel, each element having a gray level; determining, based on a maximum gray level of the plurality of elements, one or more thresholds for segmenting the image; determining one or more sub-images of a region of interest by segmenting, based on the one or more thresholds, the image; and determining, based on the one or more sub-images of the region of interest, a quality index for the image.

An OCT apparatus includes an OCT optical system that has a light splitter splitting light from an OCT light source to light travelling to a measurement light path and light travelling to a reference light path and a detector detecting a spectrum interference signal of measurement light guided to a subject eye through the measurement light path and reference light from the reference light path, and a processing unit that processes the spectrum interference signal to generate OCT data. The processing unit performs at least complementary processing on an overlapping region of a real image and a virtual image in OCT data based on a plurality of OCT data obtained with different optical path lengths when detecting the spectrum interference signal, and generates OCT data subjected to the complementary processing.

An x-ray imaging apparatus and associated methods are provided to execute multi-pass imaging scans for improved quality and workflow. An imaging scan can be segmented into multiple passes that are faster than the full imaging scan. Data received by an initial scan pass can be utilized early in the workflow and of sufficient quality for treatment setup, including while the another scan pass is executed to generate data needed for higher quality images, which may be needed for treatment planning. In one embodiment, a data acquisition and reconstruction technique is used when the detector is offset in the channel and/or axial direction for a large FOV during multiple passes.

A method of establishing an enhanced three-dimensional (3D) model of intracranial angiography is provided and includes: obtaining a bright-blood image group, a black-blood image group and an enhanced black-blood image group; preprocessing image pairs to obtain first bright-blood images and black-blood images; registering the first bright-blood image by taking the first black-blood image as reference to obtain a registered bright-blood image group; eliminating flowing void artifact to obtain an artifact-elimination enhanced black-blood image group; subtracting each image of the artifact-elimination enhanced black-blood image group from corresponding black-blood image to obtain angiography enhanced images; establishing a blood 3D model and a vascular 3D model with blood boundary expansion by using the registered bright-blood image group; establishing an angiography enhanced 3D model by using the angiography enhanced images; obtaining an enhanced 3D model of intracranial angiography based on the blood 3D model, the vascular 3D model and the angiography enhanced 3D model.