Abstract: Techniques are described that facilitate generating neural network (NNs) tailored to optimize specific properties of medical images using novel loss functions. According to an embodiment, a system is provided that comprises a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory. The computer executable components comprise a training component that trains a NN to generate a modified version of computed tomography (CT) data comprising one or more optimized properties relative to the CT data using a loss function tailored to control learning adaptation of the NN based on error attributed to one or more defined components associated with the CT data, resulting in a trained NN, wherein the one or more defined components comprise at least one of a frequency component or a spatial feature component.

Abstract: Methods and systems are provided for identifying motion in medical images. In one example, a method includes obtaining projection data of an imaging subject, reconstructing a first image of a location of the imaging subject from the projection data using a first reconstruction technique and reconstructing a second image corresponding to the same location of the imaging subject from the of projection data using a second reconstruction technique, different than the first reconstruction technique in terms of temporal sensitivity, calculating an inconsistency metric quantifying temporal inconsistencies between the first image and the second image, and taking an action based on the inconsistency metric.

Abstract: Systems and methods for obtaining images are described. A method may include detecting a patient residing on a table proximate the system and detecting one or more artifact areas within an anatomical scan range of the patient. In some examples, the method can include generating an artifact area indicator for the system to display, wherein the artifact area indicator comprises data indicating a location for each of the one or more artifact areas that reside within the anatomical scan range of the patient.

Abstract: A CT system includes a gantry having a rotatable base and having an opening for receiving an object to be scanned, an x-ray source, a CT detector, and a computer programmed to detect a mis-registration at a slab boundary between a first slab and a second slab of a reconstructed image, quantify an amount of mis-registration at the slab boundary, and adjust the reconstructed image at the slab boundary based on the quantification.

Abstract: An imaging system allows for modification of data acquisition parameters, where the parameters affect dose distribution. The system includes a library of exams, and a computer programmed to obtain a set of scanning parameters for image data acquisition and image reconstruction, obtain scan data from the library of exams that is based on a similarity metric for a patient to be scanned, simulate a new scan of the patient using the obtained scan data and using the obtained set of scanning parameters, and generate a new set of scanning parameters based on the simulation.

Abstract: An imaging system allows for modification of data acquisition parameters, where the parameters affect dose distribution. The system includes a library of exams, and a computer programmed to obtain a set of scanning parameters for image data acquisition and image reconstruction, obtain scan data from the library of exams that is based on a similarity metric for a patient to be scanned, simulate a new scan of the patient using the obtained scan data and using the obtained set of scanning parameters, and generate a new set of scanning parameters based on the simulation.

Abstract: A CT system includes a gantry having a rotatable base and having an opening for receiving an object to be scanned, an x-ray source, a CT detector, and a computer programmed to detect a mis-registration at a slab boundary between a first slab and a second slab of a reconstructed image, quantify an amount of mis-registration at the slab boundary, and adjust the reconstructed image at the slab boundary based on the quantification.