# US 12,111,376 B2 · Imaging with signal coding and structure modeling

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- Number: US 12,111,376 B2
- Document ID: US12111376B2
- Status: Granted
- Kind: B2
- Application number: 17/891,135
- Filed: 2022-08-19
- Published: 2022-12-15
- Granted: 2024-10-08
- Earliest claimed: 2017-07-20
- Applicants: Yudong Zhu
- Inventors: Yudong Zhu
- Web page: https://patentgrep.com/patent/US12111376B2

## CPC

- G01R 33/5611: {Parallel magnetic resonance imaging, e.g. sensitivity encoding [SENSE], simultaneous acquisition of spatial harmonics [SMASH], unaliasing by Fourier encoding of the overlaps using the temporal dimension [UNFOLD], k-t-broad-use linear acquisition speed-up technique [k-t-BLAST], k-t-SENSE (structural details of arrays of sub-coils G01R33/3415)}
- G01R 33/4835: {of multiple slices}
- G01R 33/543: {Control of the operation of the MR system, e.g. setting of acquisition parameters prior to or during MR data acquisition, dynamic shimming, use of one or more scout images for scan plane prescription (G01R33/546 takes precedence)}
- 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)}
- G01R 33/561: by reduction of the scanning time, i.e. fast acquiring systems, e.g. using echo-planar pulse sequences
- G01R 33/583: {Calibration of signal excitation or detection systems, e.g. for optimal RF excitation power or frequency (G01R33/246 takes precedence)}
- G01R 33/4616: {using specific RF pulses or specific modulation schemes, e.g. stochastic excitation, adiabatic RF pulses, composite pulses, binomial pulses, Shinnar-le-Roux pulses, spectrally selective pulses not being used for spatial selection}
- G01R 33/4818: {MR characterised by data acquisition along a specific k-space trajectory or by the temporal order of k-space coverage, e.g. centric or segmented coverage of k-space}
- G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12)

## Abstract

A technology is provided for multi-component and/or multi-configuration imaging with coding, signal composition, signal model, structure model, structure model learning, decoding, reconstruction, performance prediction and performance enhancement. A magnetic resonance imaging example comprises acquiring signal samples in accordance with a coding scheme and a k-space sampling scheme, identifying a structure model in a data assembly formed using an extraction operation, and generating a result consistent with both the acquired signal samples and the identified structure model.

## Claims

### Claim 1

An imaging system for imaging an object, comprising:
a hardware system for performing magnetic resonance signal excitation and detection,
a computer system electrically connected to said hardware system, comprising:
at least one display;
at least one processor; and
non-transitory computer readable media, comprising computer readable code configured to cause the at least one processor to:
devise a coding scheme for modifying the probing that a plurality of components of said object experience during imaging,
execute a set of procedures which causes said plurality of components to experience diverse probing via said coding scheme and to create at least one composite signal,
acquire said at least one composite signal,
process said at least one composite signal and reconstruct at least one image using at least one predetermined relation between said at least one composite signal and said at least one image, said processing and reconstructing comprising resolving contributions from said plurality of components,
whereby said coding, processing and reconstructing comprises a substantially integral treatment of said plurality of components,
further comprising a structure model capturing a resemblance amongst or redundancy within elements selected from the group comprising said at least one image and images obtained from additional imaging configurations,
wherein said imaging system is a magnetic resonance imaging system and said structure model captures a resemblance in the form of relative image shading.

### Claim 2

An imaging system, comprising:
a hardware system for performing magnetic resonance signal excitation and detection,
a computer system electrically connected to said hardware system, comprising:
at least one display;
at least one processor; and
non-transitory computer readable media, comprising:
computer readable code configured to cause the at least one processor to:
identify a signal model, said signal model relating signal samples detected during imaging to at least one underlying image,
conduct imaging and acquiring, with a multi-configuration setup or with a substantially sequential timing, a data set comprising said signal samples,
form a data assembly by applying an extraction operation to said data set or a functionally equivalent data set or both,
determine a structure model by learning from said data assembly, said structure model capturing a resemblance amongst or redundancy within elements selected from the group comprising said at least one underlying image and images obtained from additional imaging configurations, and
generate a result consistent with said signal samples and said structure model, said result being selected from the group comprising a spectrum, a set of spectra, an image, a set of images, a map, a set of maps, and a physical quantity distribution,
wherein said generating of the result comprises solving an optimization problem, said optimization problem having cost terms selected from the group comprising deviation from said structure model, deviation from said signal model, and deviation from any further models specifically applicable.

### Claim 3

A magnetic resonance imaging apparatus, comprising:
a. a hardware system for performing magnetic resonance signal excitation and detection,
b. a computer system electrically connected to said hardware system, comprising:
at least one display;
at least one processor; and
non-transitory computer readable media, comprising:
computer readable code for applying said magnetic resonance signal excitation and detection,
computer readable code, comprising a k-space sampling scheme or a coding scheme or both, for methodically acquiring, with a multi-configuration setup or with a substantially sequential timing, a data set comprising magnetic resonance signal samples,
computer readable code for forming a data assembly by applying an extraction operation to said data set or a functionally equivalent data set or both,
computer readable code for determining a structure model in said data assembly,
computer readable code for generating a result consistent with said signal samples and said structure model, and
computer readable code for displaying said result on said at least one display,
wherein said generating of the result comprises solving an optimization problem, said optimization problem having cost terms selected from the group comprising deviation from said structure model, deviation from said signal model, and deviation from any further models specifically applicable.

### Claim 4 (depends on 1)

The imaging system of claim 1, wherein said coding scheme comprises marking said components with modulating weights, said modulating weights being selected from the group comprising phase-modulating weights, amplitude-modulating weights, and phase- and amplitude-modulating weights.

### Claim 5 (depends on 1)

The imaging system of claim 1, wherein said set of procedures causes to create said at least one composite signal by effecting combination of experiments and superposition of signals thereof.

### Claim 6 (depends on 1)

The imaging system of claim 1, wherein said imaging system is a magnetic resonance imaging system, said reconstructing is in a space of at least one of spatial, spectral and other characteristic dimensions, and said reconstructing comprises an image reconstruction scheme taking into account said coding.

### Claim 7 (depends on 1)

The imaging system of claim 1, further including at least one of predicting noise level of said at least one image and performing optimization of the setup for said imaging.

### Claim 8 (depends on 2)

The imaging system of claim 2 wherein said determining a structure model is finding a mathematical representation selected from the group comprising a vector space, a basis, a matrix, a set of maps, a set of weights, a set of networks, a set of operators and a set of functions.

### Claim 9 (depends on 2)

The imaging system of claim 2, wherein said generating the result comprises solving a set of equations, said set of equations being selected from the group comprising expressions of constraints due to said structure model, expressions of constraints due to said signal model, and expressions of further constraints derived from physics and statistics that are specifically applicable.

### Claim 10 (depends on 2)

The imaging system of claim 2, wherein said signal model comprises a mathematical representation of coding, said coding modifying the probing that a plurality of components experience during their imaging.

### Claim 11 (depends on 2)

The imaging system of claim 2, wherein said imaging system is a magnetic resonance imaging system and said structure model captures a resemblance in the form of relative image shading.

### Claim 12 (depends on 2)

The imaging system of claim 2, wherein said generating a result uses a strategy comprising at least one of reducing whole problem into a set of smaller problems and performing a substantial amount of computation before completion of said acquiring a data set.

### Claim 13 (depends on 6)

The imaging system of claim 6, wherein said coding scheme causes said plurality of components to experience varying effects due to at least one from the group consisting radio-frequency field, gradient field, B0 field and imaging sequence timing.

### Claim 14 (depends on 6)

The imaging system of claim 6, wherein said plurality of components comprises slices distributed in spatial dimensions and said reconstructing comprises spatial mapping.

### Claim 15 (depends on 6)

The imaging system of claim 6, wherein said coding scheme comprises marking said components with modulating weights via field manipulation, said field manipulation including at least one from the group comprising radio-frequency excitation, gradient pulsing and B0 field shimming.

### Claim 16 (depends on 11)

The imaging system of claim 11, wherein said acquiring a data set is at least one operation from the group comprising detecting magnetic resonance signals with parallel radio-frequency receive channels, detecting magnetic resonance signals in a sequence of experiments each using a predetermined subset of parallel radio-frequency transmit channels, detecting magnetic resonance signals in separate experiments characterized by varying image contrast or echo timing or both.

### Claim 17 (depends on 15)

The imaging system of claim 15, wherein said field manipulation effects reduced sampling requirement and acceleration of imaging.

### Claim 18 (depends on 15)

The imaging system of claim 15, wherein said field manipulation effects field-of-view packing.