Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

A magnetic resonance imaging system (100) for acquiring magnetic resonance data (141) from an imaging zone (108) includes a memory (134, 136) for storing machine executable instructions (150, 152, 154, 156) and pulse sequence commands (140). The pulse sequence commands cause the magnetic resonance imaging system to provide at least one spatially selective saturation pulse (408, 410) to at least one selected volume (124, 124′) that is at least partially outside of a region of interest (123) and within the imaging zone. The magnetic resonance imaging system performs a non-selective inversion (412) of spins in the region of interest followed by a readout (414) of the magnetic resonance data which is reconstructed (202) into an image (142).

Embodiments of this application disclose methods, systems, and devices for image region localization and medical image processing. In one aspect, a method comprises acquiring three-dimensional images of a target body part of a patient. The three-dimensional images comprise a plurality of magnetic resonant imaging (MRI) modalities. The method comprises registering a first image set of a first modality with a second image set of a second modality. After the registering, image features of the three-dimensional images are extracted. The image features are fused to obtain fused features. The method also comprises determining voxel types corresponding to voxels in the three-dimensional images according to the fused features. The method also comprises selecting, from the three-dimensional images, target voxels having a preset voxel type, obtaining position information of the target voxels, and localizing a target region within the target body part based on the position information of the target voxels.

A magnetic resonance imaging apparatus according to an embodiment includes sequence controlling circuitry and processing circuitry. The sequence controlling circuit executes, while a k-space is divided into a plurality of segments, a pulse sequence by which a tag pulse is applied and subsequently acquisition is performed. The processing circuit generates an image based on the pulse sequence executed by the sequence controlling circuit. The pulse sequence is a pulse sequence by which the acquisition is repeatedly performed at the center of the k-space. The sequence controlling circuit executes the pulse sequence, while changing the range to which the tag pulse is applied, for each of the plurality of segments.

An image reconstruction apparatus according to an embodiment includes a processing circuitry configured to reconstruct at least one image from a plurality of pieces of k-space data acquired in a time direction. The processing circuitry performs image estimation calculation that reconstructs estimated images sharing the k-space data in the time direction, and adaptation calculation that adapts the estimated images to prior knowledge in the time direction.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

A system and method is provided for acquiring flow encoded data from a subject using a magnetic resonance imaging (MRI) system. The method includes acquiring flow encoded (FE) data with alternating encoding polarities and along two of three orthogonal directions through the subject over at least two cycles of the flow within the subject; and separating the FE data into directional FE datasets using a temporal filter that separates the FE data based on temporal modulation of the FE directions caused by the alternating encoding polarities extending over the at least two cycles of the flow within the subject that shift the Fourier spectrum of velocity waveforms corresponding to the FE data. The method also includes using the directional FE datasets to generate an image of the subject showing flow within the subject caused by the at least two cycles of flow within the subject.

Systems and methods for data transmission may be provided. The system may at least include a data transmission module. The system may obtain MR signals from one or more RF coils. The system may generate, via a first portion of the data transmitting module, first data based on the MR signals. The system may generate, via a second portion of the data transmitting module, second data based on the first data. The second portion of the data transmitting module may connect to the first portion of the data transmitting module wirelessly. The system may further store the second data in a non-transitory computer-readable storage medium.

Techniques measuring post contrast phase include collecting 3D medical imagery of a subject after injection with a contrast agent. A first set of slices is obtained in which each includes a first anatomical feature selected from a portal vein, aorta, inferior vena cava, liver, spleen or renal cortex. A second set of slices is obtained in which each includes a different second anatomical feature. A first image region is obtained from the first set and a different second image region from the second set. A trained convolutional neural network is configured to input the first image region to a first plurality of convolutional hidden layers and the second image region to a second plurality of convolutional hidden layers and output from both to a fully connected hidden layer that outputs a post contrast phase. Output data is presented based on the post contrast phase.