# US 10,307,139 B2 · System, method and computer-accessible medium for diffusion imaging acquisition and analysis

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- Number: US 10,307,139 B2
- Document ID: US10307139B2
- Status: Granted
- Kind: B2
- Application number: 15/419,508
- Filed: 2017-01-30
- Published: 2017-08-03
- Granted: 2019-06-04
- Earliest claimed: 2016-01-28
- Assignees: New York University
- Applicants: New York University
- Inventors: Fernando Boada; Steven Baete; Jingyun Chen; Ricardo Otazo
- Web page: https://patentgrep.com/patent/US10307139B2

## CPC

- A61B 8/5238: {for combining image data of patient, e.g. merging several images from different acquisition modes into one image}
- A61B 5/0042: {for the brain}
- A61B 5/0066: {Optical coherence imaging}
- A61B 5/4064: {Evaluating the brain (for intracranial pressure A61B5/031; for cerebral blood gases A61B5/14553; using EEG A61B5/369)}
- A61B 8/0808: {for diagnosis of the brain}
- A61B 8/5223: {for extracting a diagnostic or physiological parameter from medical diagnostic data (for algorithms to analyse biomedical images G06T7/0012)}
- G01R 33/5608: {Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels (image data processing or generation, in general G06T)}
- G06F 18/2135: based on approximation criteria, e.g. principal component analysis
- G06F 18/2136: based on sparsity criteria, e.g. with an overcomplete basis
- G06T 7/0014: {using an image reference approach}
- G06V 10/7715: {Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods}
- G16H 30/40: for processing medical images, e.g. editing
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- A61B 6/032: {Transmission computed tomography [CT]}
- A61B 6/501: {for diagnosis of the head, e.g. neuroimaging or craniography}
- A61B 6/5217: {extracting a diagnostic or physiological parameter from medical diagnostic data}
- A61B 6/5229: {combining image data of a patient, e.g. combining a functional image with an anatomical image}
- G01R 33/56341: {Diffusion imaging}
- G06T 2207/10092: Diffusion tensor magnetic resonance imaging [DTI]
- G06T 2207/30016: Brain
- G06V 2201/03: Recognition of patterns in medical or anatomical images
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

Exemplary system, method and computer-accessible medium for determining a difference(s) between two sets of subjects, can be provided. Using such exemplary system, method and computer-accessible medium, it is possible to receive first imaging information related to a first set of subjects of the two sets of the subjects, receive second imaging information related to a second set of subjects of the two sets of subjects, generate third information by performing a decomposition procedure(s) on the first imaging information and the second information, and determine the difference(s) based on the third information.

## Claims

### Claim 1

A non-transitory computer-accessible medium having stored thereon computer-executable instructions for determining at least one difference between at least two sets of subjects, wherein, when a computer arrangement executes the instructions, the computer arrangement is configured to perform procedures comprising:
receiving first imaging information related to at least one first set of subjects of the at least two sets of the subjects;
receiving second imaging information related to at least one second set of subjects of the at least two sets of subjects;
generating at least one first matrix based on the first imaging information and at least one second matrix based on the second imaging information, wherein columns of the at least one first matrix correspond to particular first subjects in the at least one first set of subjects, and rows of the at least one first matrix correspond to features of the particular first subjects, and wherein columns of the at least one second matrix correspond to particular second subjects in the at least one second set of subjects, and rows of the at least one second matrix correspond to features of the particular second subjects;
generating third information by performing at least one low rank plus sparse (L+S) decomposition procedure on the at least one first matrix and the at least one second matrix; and
determining the at least one difference based on the third information.

### Claim 2 (depends on 1)

The computer-accessible medium of claim 1, wherein:
the first imaging information includes a plurality of first images, and wherein a particular image of the first images corresponds to a particular first subject in the at least one first set of subjects, and
the second imaging information includes a plurality of second images, and wherein a particular image of the second images corresponds to a particular second subject in the at least one second set of subjects.

### Claim 3 (depends on 1)

The computer-accessible medium of claim 1, wherein the at least one first set of subjects is different than the at least one second set of subjects.

### Claim 4 (depends on 1)

The computer-accessible medium of claim 1, wherein the computer arrangement is configured to generate the third information by decomposing (i) the at least one first matrix into at least one first low-rank matrix and at least one first residual matrix using the L+S decomposition procedure, and (ii) the at least one second matrix into at least one second low-rank matrix and at least one second residual matrix using the L+S decomposition procedure.

### Claim 5 (depends on 4)

The computer-accessible medium of claim 4, wherein the computer arrangement is configured to determine the at least one difference based on the at least one first low-rank matrix and the at least one second low-rank matrix.

### Claim 6 (depends on 5)

The computer-accessible medium of claim 5, wherein the computer arrangement is configured to determine the at least one difference by comparing the at least one first low-rank matrix to the at least one second low-rank matrix on a voxel by voxel basis.

### Claim 7 (depends on 4)

The computer-accessible medium of claim 4, wherein the at least one first residual matrix includes outliers from the at least one first set of subjects and the at least one second residual matrix includes outliers from the at least one second set of subjects.

### Claim 8 (depends on 1)

The computer-accessible medium of claim 1, wherein the computer arrangement is further configured to co-register the first information and the second imaging information.

### Claim 9 (depends on 8)

The computer-accessible medium of claim 8, wherein the computer arrangement is further configured to map the first imaging information and the second imaging information to at least one atlas.

### Claim 10 (depends on 1)

The computer-accessible medium of claim 1, wherein the computer arrangement is further configured to generate the first imaging information and the second imaging information.

### Claim 11 (depends on 1)

The computer-accessible medium of claim 1, wherein the first imaging information and the second imaging information include at least one of magnetic resonance imaging information, computed tomography imaging information, optical coherence tomography imaging information, ultrasound imaging information or Optical Frequency Domain Reflectometry imaging information.

### Claim 12 (depends on 1)

The computer-accessible medium of claim 1, wherein the first imaging information includes a plurality of first images of brains of the at least one first set of subjects, and the second imaging information includes a plurality of second images of brains of the at least one second set of subjects.

### Claim 13 (depends on 12)

The computer-accessible medium of claim 12, wherein the at least one difference includes a presence or absence of a traumatic brain injury.

### Claim 14 (depends on 1)

The computer-accessible medium of claim 1, wherein the at least one difference includes an Orientation Distribution Function group difference.

### Claim 15

A method for determining at least one difference between at least two sets of subjects, comprising:
receiving first imaging information related to at least one first set of subjects of the at least two sets of subjects;
receiving second imaging information related to at least one second set of subjects of the at least two sets of subjects;
generating at least one first matrix based on the first imaging information and at least one second matrix based on the second imaging information, wherein columns of the at least one first matrix correspond to particular first subjects in the at least one first set of subjects, and rows of the at least one first matrix correspond to features of the particular first subjects, and wherein columns of the at least one second matrix correspond to particular second subjects in the at least one second set of subjects, and rows of the at least one second matrix correspond to features of the particular second subjects;
generating third information by performing at least one low rank plus sparse (L+S) decomposition procedure on the at least one first matrix and the at least one second matrix; and
using a specifically configured computer hardware arrangement, determining the at least one difference based on the third information.

### Claim 16

A system for determining at least one difference between at least two sets of subjects, comprising:
a computer hardware arrangement specifically configured to:
receive first imaging information related to at least one first set of subjects of the at least two sets of subjects;
receive second imaging information related to at least one second set of subjects of the at least two sets of subjects;
generate at least one first matrix based on the first imaging information and at least one second matrix based on the second imaging information, wherein columns of the at least one first matrix correspond to particular first subjects in the at least one first set of subjects, and rows of the at least one first matrix correspond to features of the particular first subjects, and wherein columns of the at least one second matrix correspond to particular second subjects in the at least one second set of subjects, and rows of the at least one second matrix correspond to features of the particular second subjects;
generate third information by performing at least one low rank plus sparse (L+S) decomposition procedure on the at least one first matrix and the at least one second matrix; and
determine the at least one difference based on the third information.