Abstract: Systems and methods to manage digital asset functionality based on fulfillment of criteria are disclosed. Exemplary implementations may: receive, from a digital asset distribution platform, an indication that a user is requesting to acquire or acquired a collectible digital asset in a digital wallet of the user, the collectible digital asset is correlated with an entity; determine whether condition(s) are fulfilled; upon determination that the condition(s) are not fulfilled, prevent the acquisition of the collectible digital asset by the digital wallet or restrict a set of rights to the correlated entity; and upon determination that the condition(s) are fulfilled, permit acquisition of the collectible digital asset or permit the set of rights.

Abstract: Exemplary embodiments of method, system and computer-accessible medium according to the present disclosure can be provided for converting magnetic resonance (MR) arterial signal intensity versus time curves to arterial input functions (AIF) with less susceptibility to artifacts such as flow-related enhancement. Exemplary methods, systems and computer-accessible medium can be used to constrain AIF to satisfies the indicator dilution principle, according to which the area under an initial pass component of AIF can be equal to the injected dose divided by the cardiac output. For example, Monte Carlo simulations of MR renography and tumor perfusion protocols can be performed for comparison with conventional methods.

Abstract: In a magnetic resonance imaging method for non-contrast imaging of blood at a region in the subject's body, a first 3D MR image is acquired represented by a first 3D volume data set of the region at a first trigger delay time. The first 3D image is acquired using a substantially 90° excitation pulse followed by a plurality of variable flip angle refocus pulses forming an echo train where the refocus pulses are smaller than or equal to 180°. To form the first 3D MR image, multiple MR slices are acquired related to the first trigger delay time to speed up the acquisition of the first image. A second 3D MR image is acquired represented by a second 3D volume data set at the same region using the same steps for acquiring the first 3D MR image except that a second trigger delay time is used which is different than the first trigger delay time. The first 3D volume data set and the second 3D volume data set are subtracted to create a third 3D volume data set.

Abstract: Exemplary embodiments of method, system and computer-accessible medium according to the present disclosure can be provided for converting magnetic resonance (MR) arterial signal intensity versus time curves to arterial input functions (AIF) with less susceptibility to artifacts such as flow-related enhancement. Exemplary methods, systems and computer-accessible medium can be used to constrain AIF to satisfies the indicator dilution principle, according to which the area under an initial pass component of AIF can be equal to the injected dose divided by the cardiac output. For example, Monte Carlo simulations of MR renography and tumor perfusion protocols can be performed for comparison with conventional methods.

Abstract: In a magnetic resonance imaging method for non-contrast imaging of blood at a region in the subject's body, a first 3D MR image is acquired represented by a first 3D volume data set of the region at a first trigger delay time. The first 3D image is acquired using a substantially 90° excitation pulse followed by a plurality of variable flip angle refocus pulses forming an echo train where the refocus pulses are smaller than or equal to 180°. To form the first 3D MR image, multiple MR slices are acquired related to the first trigger delay time to speed up the acquisition of the first image. A second 3D MR image is acquired represented by a second 3D volume data set at the same region using the same steps for acquiring the first 3D MR image except that a second trigger delay time is used which is different than the first trigger delay time. The first 3D volume data set and the second 3D volume data set are subtracted to create a third 3D volume data set.