Abstract: An exemplary system, method and computer-accessible medium for generating a denoised magnetic resonance (MR) image(s) of a portion(s) of a patient(s) can be provided, which can include, for example, generating a plurality of MR images of the portion(s), where a number of the MR images can be based on a number of MR coils in a MR apparatus used to generate the MR images, generating MR imaging information by denoising a first one of the MR images based on another one of the MR images, and generating the denoised MR image(s) based on the MR imaging information. The number of the MR coils can be a subset of a total number of the MR coils in the MR apparatus. The number of the MR coils can be a total number of the MR coils in the MR apparatus. The MR information can be generated by denoising each of the MR images based on the other one of the MR images.

Abstract: An exemplary system, method and computer-accessible medium for characterizing a microstructure of a prostate of a patient can be provided, which can include, for example, generating a magnetic resonance (MR) radiofrequency (RF) pulse(s) by varying (i) a diffusion time, (ii) a diffusion gradient direction, (iii) a diffusion gradient pulse width, or (iv) a diffusion gradient pulse shape, applying the MR RF pulse(s) to the prostate of the patient, receiving a resultant MR signal from the prostate of the patient that can be based on the MR RF pulse(s), determining information regarding a plurality of compartments for the prostate from the resultant MR signal by varying an echo time or a mixing time, and characterizing the microstructure for each of the compartments by applying a microstructural model(s) to each of the compartments.

Abstract: An exemplary system, method and computer-accessible medium for characterizing a microstructure of a prostate of a patient can be provided, which can include, for example, generating a magnetic resonance (MR) radiofrequency (RF) pulse(s) by varying (i) a diffusion time, (ii) a diffusion gradient direction, (iii) a diffusion gradient pulse width, or (iv) a diffusion gradient pulse shape, applying the MR RF pulse(s) to the prostate of the patient, receiving a resultant MR signal from the prostate of the patient that can be based on the MR RF pulse(s), determining information regarding a plurality of compartments for the prostate from the resultant MR signal by varying an echo time or a mixing time, and characterizing the microstructure for each of the compartments by applying a microstructural model(s) to each of the compartments.

Abstract: An exemplary system, method and computer-accessible medium for generating a denoised magnetic resonance (MR) image(s) of a portion(s) of a patient(s) can be provided, which can include, for example, generating a plurality of MR images of the portion(s), where a number of the MR images can be based on a number of MR coils in a MR apparatus used to generate the MR images, generating MR imaging information by denoising a first one of the MR images based on another one of the MR images, and generating the denoised MR image(s) based on the MR imaging information. The number of the MR coils can be a subset of a total number of the MR coils in the MR apparatus. The number of the MR coils can be a total number of the MR coils in the MR apparatus. The MR information can be generated by denoising each of the MR images based on the other one of the MR images.

Abstract: An exemplary system, method and computer-accessible medium for removing noise and Gibbs ringing from a magnetic resonance (“MR”) image(s), can be provided, which can include, for example, receiving information related to the MR image(s), receiving information related to the MR image(s), and removing the Gibbs ringing from the information by extrapolating data in a k-space from the MR image(s) beyond an edge(s) of a measured portion of the k-space. The data can be extrapolated by formatting the data as a regularized minimization problem(s). A first weighted term of the regularized minimization problem(s) can preserve a fidelity of the extrapolated data, and a second weighted term of the regularized minimization problem(s) can be a penalty term that can be based a norm(s) of the MR image(s), which can be presumed to be sparse.

Abstract: An exemplary system, method and computer-accessible medium for determining a plurality of tissue parameters of a tissue(s), can include, for example, receiving information related to a plurality of rotational invariants contained within a diffusion magnetic resonance (dMR) image(s) of the tissue(s), and generating the tissue parameters using a set of rotational invariants related to the plurality of tissue parameters using such information. The tissue parameters can be generated by factorizing a response of an individual fiber segment of the tissue(s) based on the set of rotational invariants. The response of the individual fiber segments can be factorized from an orientational distribution function (“ODF”). The individual fiber segments can be factorized using a scalar tensor factorization(s) of the rotational invariants. The set of rotational invariants can be of a rotation group SO(3).

Abstract: Exemplary method, system, and computer-accessible medium can be provided for determining a measure of diffusional kurtosis by receiving data relating to at least one diffusion weighted image, and determining a measure of a diffusional kurtosis as a function of the received data using a closed form solution procedure. In accordance with certain exemplary embodiments of the present disclosure, provided herein are computer-accessible medium, systems and methods for, e.g., imaging in an MRI system, and, more particularly for facilitating estimation of tensors and tensor-derived measures in diffusional kurtosis imaging (DKI). For example, DKI can facilitate a characterization of non-Gaussian diffusion of water molecules in biological tissues. The diffusion and kurtosis tensors parameterizing the DKI model can typically be estimated via unconstrained least squares (LS) methods.

Abstract: An exemplary system, method and computer-accessible medium for removing noise and Gibbs ringing from a magnetic resonance (“MR”) image(s), can be provided, which can include, for example, receiving information related to the MR image(s), receiving information related to the MR image(s), and removing the Gibbs ringing from the information by extrapolating data in a k-space from the MR image(s) beyond an edge(s) of a measured portion of the k-space. The data can be extrapolated by formatting the data as a regularized minimization problem(s).

Abstract: Method, system and computer-accessible medium for determining at least one of axonal loss or myelin degradation can be provided. For example, it is possible to receive data based on at least one of a measure of diffusion of an axonal structure or a measure of a density of axons, and determine axonal loss and/or myelin degradation based on the data. The determination can be based on axonal geometry of at least one parallel tube.

Abstract: An exemplary system, method and computer-accessible medium for determining a plurality of tissue parameters of a tissue(s), can include, for example, receiving information related to a plurality of rotational invariants contained within a diffusion magnetic resonance (dMR) image(s) of the tissue(s), and generating the tissue parameters using a set of rotational invariants related to the plurality of tissue parameters using such information. The tissue parameters can be generated by factorizing a response of an individual fiber segment of the tissue(s) based on the set of rotational invariants. The response of the individual fiber segments can be factorized from an orientational distribution function (“ODF”). The individual fiber segments can be factorized using a scalar tensor factorization(s) of the rotational invariants. The set of rotational invariants can be of a rotation group SO(3).

Abstract: Exemplary embodiments of a methodology, procedure, system, method and computer-accessible medium can be provided to obtain particular information relating to at least one transport property of a material containing at least one membrane, and to determine, e.g., a permeability of the membrane of the material and/or a surface area of the membrane of the material, as a function of, e.g., the obtained particular information.

Abstract: Exemplary method, system, and computer-accessible medium can be provided for determining a measure of diffusional kurtosis by receiving data relating to at least one diffusion weighted image, and determining a measure of a diffusional kurtosis as a function of the received data using a closed form solution procedure. In accordance with certain exemplary embodiments of the present disclosure, provided herein are computer-accessible medium, systems and methods for, e.g., imaging in an MRI system, and, more particularly for facilitating estimation of tensors and tensor-derived measures in diffusional kurtosis imaging (DKI). For example, DKI can facilitate a characterization of non-Gaussian diffusion of water molecules in biological tissues. The diffusion and kurtosis tensors parameterizing the DKI model can typically be estimated via unconstrained least squares (LS) methods.

Abstract: Method, system and computer-accessible medium for determining at least one of axonal loss or myelin degradation can be provided. For example, it is possible to receive data based on at least one of a measure of diffusion of an axonal structure or a measure of a density of axons, and determine axonal loss and/or myelin degradation based on the data. The determination can be based on axonal geometry of at least one parallel tube.

Abstract: Exemplary method, system, and computer-accessible medium can be provided for determining a measure of diffusional kurtosis by receiving data relating to at least one diffusion weighted image, and determining a measure of a diffusional kurtosis as a function of the received data using a closed form solution procedure. In accordance with certain exemplary embodiments of the present disclosure, provided herein are computer-accessible medium, systems and methods for, e.g., imaging in an MRI system, and, more particularly for facilitating estimation of tensors and tensor-derived measures in diffusional kurtosis imaging (DKI). For example, DKI can facilitate a characterization of non-Gaussian diffusion of water molecules in biological tissues. The diffusion and kurtosis tensors parameterizing the DKI model can typically be estimated via unconstrained least squares (LS) methods.

Abstract: Exemplary embodiments of a methodology, procedure, system, method and computer-accessible medium can be provided to obtain particular information relating to at least one transport property of a material containing at least one membrane, and to determine, e.g., a permeability of the membrane of the material and/or a surface area of the membrane of the material, as a function of, e.g., the obtained particular information.

Abstract: Exemplary method, system, and computer-accessible medium can be provided for determining a measure of diffusional kurtosis by receiving data relating to at least one diffusion weighted image, and determining a measure of a diffusional kurtosis as a function of the received data using a closed form solution procedure. In accordance with certain exemplary embodiments of the present disclosure, provided herein are computer-accessible medium, systems and methods for, e.g., imaging in an MRI system, and, more particularly for facilitating estimation of tensors and tensor-derived measures in diffusional kurtosis imaging (DKI). For example, DKI can facilitate a characterization of non-Gaussian diffusion of water molecules in biological tissues. The diffusion and kurtosis tensors parameterizing the DKI model can typically be estimated via unconstrained least squares (LS) methods.