A medical report natural language model includes an artificial neural network implemented via the processor and is trained based a plurality of medical reports wherein each of the medical reports is mapped to at least one medical code of a plurality of medical codes and further based a plurality of medical condition terms from a plurality of alias mapping pairs, wherein each of the plurality of medical condition terms are unique, wherein each of the plurality of medical condition terms indicates a corresponding medical condition and wherein each of the plurality of alias mapping pairs includes a one of the plurality of medical condition terms and a corresponding single one of the plurality of medical codes that is a deterministic function of the one of the plurality of medical condition terms and wherein the plurality of alias mapping pairs includes two or more alias mapping pairs that map a corresponding two or more of the plurality of medical condition terms to a same one of the plurality of medical codes. A system operates by determining a first medical code of the plurality of medical codes utilizing the medical report natural language model on the first medical report by: recognizing, via the artificial neural network of the medical report natural language model, a first medical condition term of the plurality of medical condition terms in the first medical report; and determining the first medical code of the plurality of medical codes, based on the plurality of alias mapping pairs, wherein the determining the first medical code includes identifying a first alias mapping pair of the plurality of alias mapping pairs that pairs the first medical condition term deterministically to the first medical code; and mapping the first medical code of the plurality of medical codes and the first medical condition term of the plurality of medical condition terms to a first medical scan corresponding to the first medical report.

The present disclosure relates to a method for analyzing an R-wave of an electrocardiogram (ECG) signal. The method includes obtaining an original ECG signal of a subject; filtering the original ECG signal; determining whether to trigger a search gate based on the filtered ECG signal, wherein the search gate is an instruction for detecting an R-wave on the original ECG signal; and detecting the R-wave on the original ECG signal in response to a determination of triggering the search gate.

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 medical scan natural language analysis system is operable to generate a medical report natural language model based on a selected set of medical reports of the plurality of medical reports and the at least one medical code mapped to each of the selected set of medical reports. A medical report that is not included in the selected set is received via a network. A medical code is determined by utilizing the medical report natural language model on the first medical report. The medical code is mapped to a medical scan corresponding to the medical report.

There is disclosed an image processing apparatus including a hardware processor which generates a highly resolved still image from a plurality of frame images obtained by continuously imaging a moving subject. The hardware processor analyzes each of the plurality of frame images to calculate a feature amount, and determines, on a basis of the calculated feature amount, a reference frame image which becomes a reference when generating the highly resolved still image from the plurality of frame images.

A non-transitory recording medium storing a computer readable program that causes a computer of a moving image management apparatus, which manages a radiographic moving image, to perform: obtaining that is obtaining a first radiographic moving image and a second radiographic moving image, the first radiographic moving image showing a movement of a subject while breathing is repeated a first number of times per unit time, and the second radiographic moving image showing a movement of the subject while breathing is repeated a second number of times that is different from the first number of times per the unit time; and associating that is associating respective numbers of breaths during imagings with the first radiographic moving image and the second radiographic moving image that are obtained in the obtaining.

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.

A method for determining a quantitative result CT parameter map in a region of interest of an object under examination is described. The method includes acquiring a sequence of quantitative input CT parameter maps for at least two predetermined times, the sequence being generated by a contrast-enhanced spectral multiphase CT of the region of interest; receiving a sequence of contrast-enhanced MRI image datasets, the MRI datasets having a higher temporal resolution than the sequence of input CT parameter maps; determining a relation between the MRI image datasets and the input CT parameter maps; and determining the result CT parameter map based on the determined relation and the MRI image datasets for at least one additional time, the at least one additional time being different from the predetermined time.

A method for gating in tomographic imaging system includes steps of: (a) performing a tomographic imaging on an object with a target moving periodically along a first axis for acquiring projection images; (b) obtaining projected curves by summing up pixel values along a direction of a second axis perpendicular to the first axis in each projection image; (c) determining a target zone on the projection images, wherein a central position on the first axis of the target zone is corresponding to a position having the largest variation in the projected curves on the first axis; (d) calculating parameter values of pixel values in the target zones and obtaining a curve of a moving cycle of the target according to the parameter values; and (e) selecting the projection images under the same state in the moving cycle for image reconstruction according to the curve of the moving cycle of the target.

Methods and systems are provided for dynamically visualizing an object of interest that includes part of the vasculature of a patient, which employ a 3D model of the object to generate at least one roadmap that includes information that characterizes properties of the object (such as centerlines, contours, and an image mask. Reference location(s) corresponding to the roadmap(s) are determined for an interventional device used to treat the object. In an online phase, non-contrast-enhanced x-ray image data of the object are obtained and processed to determine location of the interventional device in the image data, and a particular roadmap is selected or accessed. The reference location corresponding to the particular roadmap and the determined location of interventional device are used to transform the particular roadmap. A visual representation of the transformed roadmap is overlaid on the image data for display.