Various systems and computer-implemented methods for background radiation based attenuation correction are disclosed. A first set of nuclear scan data including first scan data associated with a first imaging modality having a long-axial field of view and first background radiation data is received and a first background radiation attenuation map is generated by applying a trained machine-learning model to the first background radiation data. A first set of attenuation corrected scan data is generated by performing attenuation correction of the first scan data based only on the first background radiation attenuation map and a first image is reconstructed from the first set of attenuation corrected scan data. The disclosed background radiation based attenuation correction may be used for longer duration scans, repeat scans, and/or low-dose clinical applications, such as pediatric applications, theranostics, and/or other suitable applications.

A method for signal separation includes obtaining list mode data representing radiation detected during an imaging scan, the list mode data being affected by quasi-periodic motion of an imaging object; dividing the list mode data into first non-overlapping frames of a first frame length, and process the first frames to determine a cardiac cycle length; determining a second frame length, longer than the first frame length, based on the determined cardiac cycle length; re-binning the list mode data into overlapping frames having the second frame length, based on the non-overlapping frames having the first frame length; applying a principal component analysis (PCA) process on the re-binned list mode data having the second frame length to determine a respiratory waveform; determining a cardiac waveform using the determined respiratory waveform; and reconstructing an image based on the list mode data using the determined respiratory waveform and the determined cardiac waveform.

A medical imaging system is provided. Imaging detector columns are installed in a gantry to receive imaging information about a subject. Imaging detector columns can extend and retract radially as well as be rotated orbitally around the gantry. The system can automatically adjust setup configuration and an imaging operation based on subject shape estimation information.

A positron emission tomography-magnetic resonance (PET-MR) system is provided. The PET-MR system includes an MR subsystem, a PET subsystem, and a protocol adjustment system. The protocol adjustment system includes a protocol adjustment computing device having at least one processor programmed to receive a protocol. The protocol includes a scanning task list including a PET scanning task of a bed and MR scanning tasks of the bed and to be performed simultaneously with the PET scanning task. The protocol also includes a combination list indicating MR data acquired by an MR scanning task of one bed are to be combined with MR data acquired by the same MR scanning task of another bed. The at least one processor is further programmed to adjust the protocol based on the combination list by processing the one or more MR scanning tasks based on the combination list.

Systems and methods for reconstruction for a medical imaging system. A scaling factor is used during the reconstruction process to adjust a step size of a gradient update. The adjustment of the step size of the gradient provides the ability to adjust a level of denoising by the reconstruction process.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for machine learning image reconstruction. In some implementations, first input data representing the image of the one or more internal structures generated using a first imaging device is provided as input to a first machine learning model having one or more fully-connected layers. First output data generated by the first machine learning model is obtained and the first output data together with second input data representing a second image of the one or more internal structures generated using a second imaging device is provided to a second machine learning model having one or more convolutional layers. Second output data generated by the second machine learning model is obtained and used to generate rendering data that, when processed by a computing device, causes the computing device to output a reconstructed image.

A method, system, processing circuitry, and computer program product for providing initial motion correction in magnetic resonant imaging (MRI) data that enables additional image correction to be performed on subsequently processed MRI data in the same imaging set. One such method receives k-space data including a first set of motion corrupted k-space data and a second set of k-space data (different than the first set); generates motion correction data based on the first set of motion corrupted k-space data; and generates an image based on the second set of undersampled k-space data and the motion correction data.

A system and method for producing a computed tomography (CT) medical image includes receiving x-rays passing through an object with a photon-counting detector system, which includes a plurality of detector pixels configured to generate a photon-counting signal in response to receiving each photon of the x-rays having passed through the object. The method also includes summing a charge associated with each photon received at a given detector pixel of the plurality of pixels to generate a charge integration signal, utilizing the charge integration signal to correct a count of the photon-counting signal for pileup-induced count losses to create a corrected photon-counting signal, and reconstructing an image of the object using the corrected photon-counting signal.

A method for scatter estimation in a CT including a detector having multiple detector pixels includes: obtaining projection data by scanning an imaging object; reconstructing image data from the projection data; estimating, based on the projection data, a first scatter distribution; selecting, based on the first scatter distribution, a first subset of the pixels; calculating, based on the projection data and the image data, a second scatter distribution with respect to the selected first subset, the second scatter distribution having higher accuracy than the first scatter distribution; acquiring, based on the second scatter distribution, a third scatter distribution with respect to a second subset of the pixels, the third scatter distribution having higher spatial resolution than the second scatter distribution.

Systems, apparatus, articles of manufacture, and methods are disclosed to sharpen a radiographic image by capturing a radiographic image with a detector receiving a beam from a source and performing a digital correction to the radiographic image to generate a digital image with increased uniformity in sharpness compared to the radiographic image.