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.

A computer implemented method for determining a two dimensional DRR referred to as dynamic DRR based on a 4D-CT, the 4D-CT describing a sequence of three dimensional medical computer tomographic images of an anatomical body part of a patient, the images being referred to as sequence CTs, the 4D-CT representing the anatomical body part at different points in time, the anatomical body part comprising at least one primary anatomical element and secondary anatomical elements, the computer implemented method comprising the following steps: acquiring the 4D-CT; acquiring a planning CT, the planning CT being a three dimensional image used for planning of a treatment of the patient, the planning CT being acquired based on at least one of the sequence CTs or independently from the 4D-CT, acquiring a three dimensional image, referred to as undynamic CT, from the 4D-CT, the undynamic CT comprising at least one first image element representing the at least one primary anatomical element and second image elements representing the secondary anatomical elements; acquiring at least one trajectory, referred to as primary trajectory, based on the 4D-CT, the at least one primary trajectory describing a path of the at least one first image element as a function of time; acquiring trajectories of the second image elements, referred to as secondary trajectories, based on the 4D-CT; for the image elements of the undynamic CT, determining trajectory similarity values based on the at least one primary trajectory and the secondary trajectories, the trajectory similarity values respectively describing a measure of similarity between a respective one of the secondary trajectories and the at least one primary trajectory; determining the dynamic DRR by using the determined trajectory similarity values, and, in case the planning CT is acquired independently from the 4D-CT, further using a transformation referred to as planning transformation from the undynamic CT to the planning CT, at least a part of image values of image elements of the dynamic DRR being determined by using the trajectory similarity values.

A system to generate images based on imaging data of a portion of a body and physiological event data associated with a physiological process of the body. The system is to identify a plurality of physiological cycles based on the physiological event data, determine a duration of each of the plurality of physiological cycles, determine a representative duration based on the durations of each of the plurality of physiological cycles, identify a first plurality of the plurality of physiological cycles based on a difference between the durations of the first plurality of physiological cycles and the representative duration, identify a second plurality of the plurality of physiological cycles different from the first plurality of the plurality of physiological cycles, determine a predetermined number of portions of each of the second plurality of the plurality of physiological cycles, accumulate imaging data acquired during respective portions of each of the second plurality of the plurality of physiological cycles to determine a set of accumulated imaging data for each of the predetermined number of portions, and generate a plurality of images, each of the plurality of images being generated based on a respective one of the sets of accumulated imaging data.

An imaging system (100) includes a subject support (114) that supports a subject in an examination region (106). The imaging system further includes a detector (112) that detects a signal traversing the examination region, generating an output indicative of the examination region. The imaging system further includes a subject motion sensing system (118) that includes an optical system (206, 208, 214) that detects motion of the subject in the examination region and generates motion data indicative thereof. The imaging system further includes a console (122) that controls at least one of data acquisition or reconstruction based on the motion data.

Described herein are technologies for facilitating reconstruction of flow data. In accordance with one aspect, the framework receives a four-dimensional projection image dataset and registers one or more pairs of temporally adjacent projection images in the image dataset. Two-dimensional flow maps may be determined based on the registered pairs. The framework may then sort the two-dimensional flow maps according to heart phases, and reconstruct a three-dimensional flow map based on the sorted two-dimensional flow maps.

Images that are associated with an identification of a tracking target of a patient to receive radiation treatment may be received. The images may be sorted into a sequence based on a motion of the patient. The sorted images may be provided via a graphical user interface. The sequence of the sorted images that are based on the motion of the patient may be provided.

Method and systems are provided for characterizing blood flow in an atrioventricular valve of the human heart, the atrioventricular valve connecting an atrium with a corresponding ventricle of the heart, the ventricle being fluidly coupled to a particular vessel that transports blood outside the ventricle blood, which involve obtaining image data of the heart and identifying contours of the atrium and a region within the particular vessel within the image data. A time-density curve for the atrium can be calculated from the contour of the atrium and densitometric image data derived from the image data. A time-density curve for the region of the particular vessel can be calculated from the contour of the vessel region and the densitometric image data. Data that characterizes at least one regurgitation fraction related to the atrioventricular valve can be calculated from such time-density curves.

A method for determining respiratory induced blood mass change from a four-dimensional computed tomography (4D CT) includes receiving a 4D CT image set which contains a first three-dimensional computed tomographic image (3D CT) and a second 3D CT image. The method includes executing a deformable image registration (DIR) function on the received 4D CT image set, and determining a displacement vector field indicative of the lung motion induced by patient respiration. The method further includes segmenting the received 3D CT images into a first segmented image and a second segmented. The method includes determining the change in blood mass between the first 3D CT image and the second 3D CT image from the DIR solution, the segmented images, and measured CT densities.

Motion compensated reconstruction is currently not well-suited for reconstructing the valve, the valve leaflets and the neighboring vascular anatomy of the heart. Blurring of the valve and the valve leaflets occurs. This may lead to wrong diagnosis. A new approach for motion compensated reconstruction of the valve and the related anatomy is presented in which an edge-enhancing step is performed to suppress blurring.

A medical scan report labeling system is operable to transmit a medical report that includes natural language text to a first client device for display. Identified medical condition term data is received from the first client device in response. An alias mapping pair in a medical label alias database is identified by determining that a medical condition term of the alias mapping pair compares favorably to the identified medical condition term data. A medical code that corresponds to the alias mapping pair and a medical scan that corresponds to the medical report are transmitted to a second client device of an expert user for display, and accuracy data is received from the second client device in response. The medical code is mapped to the first medical scan in the medical scan database when the accuracy data indicates that the medical code compares favorably to the medical scan.