An approach to estimate noise, Rician signal bias and true signal in magnitude signal data obtained with magnetic resonance imaging. The method uses multiple measurements at different scan parameter settings, also referred to as weightings, and an iterative algorithm to estimate noise, expected signal and associated Rician signal bias. Measurements at all measured weighting levels contribute to the ultimate estimation of the bias-free signal decay function. Therefore, of the so processed magnetic resonance image data, weighted signals can be computed at arbitrary weighting levels and with considerably better signal-to-noise ratio than the originally obtained data at corresponding weightings. Bias-free weighted image data at desired weighting levels, maps of the decay function fit parameters, or maps of a combination of such decay function parameters can be used for rapid and highly sensitive tissue characterization.

Systems and methods providing enhancements to quantitative imaging systems and techniques are described herein. In one aspect, a system for tissue quantification in magnetic resonance fingerprinting (MRF) comprises a feature extraction module operable to convert pixel input high-dimensional signal evolution in to a low-dimensional feature map. The system also comprises a spatially constrained quantification module operable to capture spatial information from the low-dimensional feature map and generate an estimated tissue property map.

An MRI device for executing an imaging operation at least three times or more with a different combination of at least a repetition time and a flip angle in the same imaging sequence, includes: a receiving unit which receives information specifying an imaging target and a constraint condition relating to an imaging time or quantitative value accuracy; and a scan parameter set generation unit which calculates at least three or more scan parameter sets having a different combination of at least the repetition time and the flip angle on the basis of the constraint condition. The MRI device uses three or more scan parameter sets generated by the optimal scan parameter set generation unit and calculates quantitative values (T1, T2,and the like) of the imaging target from a plurality of images obtained by the imaging operation.

Two or more learning images generated for a first subject or a second subject and one or more correct answer images generated for the second subject or a third subject are received. In a case where pixel values of corresponding pixels of the two or more learning images are synthesized by using a synthesis parameter value, the parameter value at which the synthesized pixel values are close to a pixel value of a corresponding pixel of the correct answer image is obtained. An image generated for the first subject and having the same type as the two or more learning images is received as an examination target image. A synthesized image desired by a user is generated by synthesizing pixel values of corresponding pixels of the two or more examination target images by using the synthesis parameter value.

Methods for data acquisition and processing of magnetic resonance (MR) imaging to obtain the oxygen saturation (O2sat) of blood using a relationship between transverse relaxation time (T2) of blood and oxygen saturation. The method includes obtaining multiple images at various T2 preparation times. Next, non-linear curve fitting may be used to solve for arterial or venous O2sat. The disclosure provides a calibration-free method for accurate quantitative assessment of blood in the heart and deep vessels, even in locations having limited accessibility with other diagnostic techniques.

In various embodiments, the present invention teaches systems and methods for using T1-weighted black-blood MR imaging, with which a CVT can be well isolated from the surrounding tissues due to the signal suppression of flowing blood. In some embodiments, the invention teaches using black-blood imaging (3D variable-flip-angle turbo spin-echo acquisition) to directly visualize thrombi. In certain embodiments, the invention teaches using T1 weighted image contrast and isotropic sub-millimeter spatial resolution for accurate detection and staging of thrombi. In various embodiments, the invention allows for the detection of chronic thrombosis recanalization.

Provided herein are methods and systems for high-resolution, cerebrospinal fluid-suppressed T2*-weighted magnetic resonance imaging of cortical lesions.

In a method of performing magnetic resonance (MR) imaging, an MR apparatus, and a computer-readable medium during a first cardiac cycle of a subject, a first imaging sequence is generated for application to a subject. The first imaging sequence has a preparatory pulse and an inversion recovery pulse following the preparatory pulse. First signals emitted from the subject in response to the first imaging sequence are detected, and first image data are generated based on the first signals. During a second cardiac cycle following the first cardiac cycle, a second imaging sequence is generated for application to the subject. The second imaging sequence has a preparatory pulse. Second signals emitted from the subject in response to the second imaging sequence are detected, and second image data are generated based on the second signals.

This present invention relates to an MRI scanning assembly and a method for fusing MRI images of a target thereby generating and providing high resolution, high contrast fused MRI images. The MRI images of the target are generated by different MRI devices operating at different magnetic field intensities. A method is also described for fusing MRI images generated by an MRI device operating with different operational parameters and operational protocols.

Devices and methods are provided for analyzing images from a magnetic resonance (MR) system. The device includes at least one hardware processor coupled with a storage system accessible to the at least one hardware processor. The device further includes a display in communication with the at least one hardware processor. The device receives a plurality of non-contrast MR images in a region of interest (ROI). The device obtains blood flow signals from the plurality of non-contrast MR images. The device identifies an abnormal segment by analyzing the blood flow signals. The device displays the non-contrast MR images by a highlighted segment in at least one of the non-contrast MR images to indicate the abnormal segment on the display.