CN112763956B - Method for increasing dynamic range of magnetic resonance signal by scrambling technique - Google Patents
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Abstract
The invention discloses a method for enhancing the dynamic range of magnetic resonance signals by a scrambling technology, which comprises the following steps: s1, adding noise scrambling sources distributed in the m 1-m 2MHz interval at the signal input end of the magnetic resonance signal acquisition board, wherein the amplitude of the noise scrambling sources is n LSBs; s2, performing analog-to-digital conversion on the magnetic resonance signal mixed with the noise scrambling source; s3, acquiring a signal at the signal output end of the magnetic resonance signal acquisition board and inputting the signal into a notch filter, and removing extra frequency spectrum components introduced by a noise scrambling source through the notch filter; and S4, performing quadrature demodulation and decimation filtering on the signals. The invention applies a noise interference source to be mixed into the receiving signal of the magnetic resonance signal acquisition unit, reduces the distortion harmonic component of the analog-to-digital converter caused by coherent sampling and quantization error in the sampling and quantization process, and improves the stray-free dynamic range of the magnetic resonance analog-to-digital converter, thereby improving the dynamic range of the magnetic resonance signal.
Description
Technical Field
The invention belongs to the technical field of electronic information, and particularly relates to a method for enhancing a dynamic range of a magnetic resonance signal through a scrambling technology.
Background
The study of the Dither technology, which is translated into Chinese, namely 'jitter' or 'scrambling', originated in the middle of the twentieth century, Goodall WM in 1951 firstly proposed the Dither technology, and when a certain amount of Dither signals and input signals are introduced into a PCM system to reproduce television images, the introduction of the Dither signals is found not only to not deteriorate the quality of the images, but also to eliminate image contours generated by quantization errors, so that the image effect seen by naked eyes is more perfect, and therefore the Dither technology can be used in the PCM (pulse code modulation) system to reduce the image contour effect generated by the quantization errors. On the basis, in 1956, Widrow proposes that a diter signal is used for an external input signal of a quantizer, the nonlinear characteristic of the quantizer is eliminated, the problem of system energy consumption when sampling and quantizing are carried out at a Nyquist sampling frequency point is further researched, and the fact that the system energy consumption is minimum when the diter signal and the input signal are statistically independent is found.
In the 60 s to 70 s, the diter technology has been widely used and developed. In 1962, Robert then further studied the improvement of image edge contour effect by Dither technology, and first proposed an addition-subtraction type Dither model. He found that the diter technique can improve image quality by introducing the diter signal before quantization encoding of the image and then subtracting the diter signal after quantization. In the same year, Spang and Schulteiss firstly propose adding a diter signal to the input end of the ADC and researching the frequency spectrum change of the output signal of the ADC. The results show that adding the diter signal reduces the noise in the specified frequency domain, but increases the overall noise. In 1964, Leonard Schuchman studied the optimal selection principle of the Dither signal, and found out through theoretical derivation that the Dither signal and the input signal can be used as the optimal disturbance signal when they are statistically independent. In 1972, Jayant N S and Rabiner L R apply the diter technology to the processing of voice signals, and the addition of the diter signal can break the dependency of a quantization error sequence on input signals under the condition of ensuring that the variance of quantization errors is not increased in the process of sampling and quantizing scrambled voice signals, thereby improving the quality of the voice signals. In 1987, Locanthi and Blesser first proposed a narrow-band Dither concept, and analyzed the improvement effect of the quantizer by adding a narrow-band Dither signal, which is a band-limited Dither signal near the Nevirast frequency, to the input signal of the quantizer. The result shows that the quantizer is best in improvement effect by controlling the amplitude of the narrow-band Dither signal to be 4-5 LSB.
In the beginning of the last 21 st century of the 20 th century, much research has been conducted on the diter technique for improving harmonic components and various nonlinear characteristics of the spectrum of the ADC quantized output signal. In 1989, Wagdy M F studied the relationship between the ADC quantization error and the input signal, and found that there is a correlation between the quantization error and the input signal. Then, the influence of different types of Dither signals on the ADC quantization error and the frequency spectrum of the output signal is researched, and the influence of different types of Dither signals on the frequency spectrum of the output signal is found to be different. In 1993, Wagdy M F and Goff M first proposed the digital diter concept, found that the Spurious Free Dynamic Range (SFDR) of an ADC can be linearized by combining the analog diter signal and the digital diter signal as a diter scrambled signal, and studied in this document the offset between the characteristic curves of ADCs inputting different diter signals and the ideal ADC characteristic curve. In 1998, Wagdy formulated a standard in the literature for the evaluation of ADC bias to determine whether diter would have an effect on the quantization error of the ADC. In 2005, Jacomet M, Goette J et al discovered that diter could improve the performance of a lossy Sigma-delta modulator by introducing an external diter signal to the modulator, and verified the simulation on an FPGA development board. In 2010, Yang S, Cheng J et al propose a new digital background calibration algorithm based on diter, which can reduce the error caused by the nonlinear characteristic of ADC, and improve the spurious-free dynamic range to 76.56 dB.
In recent years, the development of Dither technology has tended to be a multi-field study and various new methods for Dither have been proposed. In 2012, Sanyal a et al, by analyzing the tone generation in the output spectrum of the multi-bit mismatch digital-to-analog converter (DAC) of the Vector Quantizer (VQ), found that adding dither to the input of the vector quantizer can eliminate the tone in the output spectrum and can achieve better mismatch shaping performance at lower hardware cost. In 2012 Yu sh et al proposed a novel feedback dithering scheme. In this scheme the dither signal is generated by quantization noise fed by the resonator and comparator and is presented in binary form. Through testing of the scheme, the fed-back binary dithering scheme has the outstanding advantages that not only in-band quantization noise can be eliminated, but also the linear characteristic of a quantizer can be effectively randomized. In 2013, Chen N, Yang SP et al applied the Dither technique to a fault detection system, and found that scrambling enables the system to obtain a higher fault detection rate under a weak signal-to-noise ratio by performing scrambling test on a fault diagnosis signal with an amplitude smaller than a quantization interval. In 2016, Eielsen AA et al applied the Dither technique to a precision electromechanical control system, reduced quantization noise and harmonic distortion by superimposing a small noise Dither and a large number of high frequency periodic Dither signals, and verified in a closed loop positioning system, finding that the Dither technique well reduced noise. On the basis, the team also proposes that a large-amplitude high-frequency periodic jitter diter signal is introduced into an ADC input end, different filters are adopted for attenuation after quantization, and the external diter technology is found to be capable of reducing harmonic distortion caused by mismatching of elements in the ADC and achieving the effect of smoothing nonlinear errors. In 2016, Ran H et al proposed a different dithering method, i.e., applying an orthogonal transform to the sample vector prior to quantization and applying its inverse to the output of the quantizer to complete the dithering. The results show that for any quantization rate, the architecture proposed therein has a second order independence, i.e. the quantization error and the correlation of the input signal gradually vanishes as the dimension of the vector of processed samples increases.
The research of the domestic scrambling technology originated in the early twenty-first century. In 2000, zhangqingmin et al, university of Nanjing technology, constructed a hierarchical flash pipeline ADC model, analyzed the improvement of harmonic distortion caused by quantization error of ADC by Dither signals, and obtained the purpose that SFDR can be improved by scrambling. In 2005, huangyouyong et al of the university of electronic technology have focused on the sampling and quantization process of ADCs, analyzed how the diter signal is sampled, improved the performance of ADCs during quantization, and built a 10-bit ADC converter for simulation verification. In 2009, cheng jing et al of the science and technology university of west ann building concluded that the diter signal can improve the non-linear characteristics of the ADC by theoretical derivation and simulation verification of the specified scrambled signal. In 2011, zhang yun et al, university of electronic technology, applied the diter technique to an improved pipelined ADC structure, and found that the addition of the diter signal can effectively ensure that the scrambled signal does not overflow by adding the residual error after the first subset of the pipelined ADC and introducing the diter signal with a certain amplitude externally. In 2014, liu xin et al of the university of sichuan rationale used 3 typically distributed diter signals as input disturbance signals of the ADC, and studied the improvement of the three diter signals on the quantization error of the ADC, so as to draw a conclusion that the uniformly distributed diter signals can effectively improve the performance of the ADC. In 2015, Chen Xiao Chong et al of chemical defense research institute applied the Dither technology to digital multi-channel, and found that the indexes are all well improved by constructing a scrambled digital multi-channel system in Simulink and analyzing the changes of differential nonlinearity and integral nonlinearity indexes before and after scrambling.
Due to the inherent non-linear characteristic of the ADC, quantization error of the ADC and an input signal have certain correlation, and the correlation can cause harmonic distortion of an output signal spectrum of the ADC, so that the spurious-free dynamic range of the ADC is seriously influenced. The addition of an external diter disturbance signal can break the correlation, randomize the periodic distribution of quantization errors, and reduce harmonics in a spectrogram, thereby improving the spurious-free dynamic performance index of the ADC.
From the current research situation and development trend, it can be seen that improving the performance index of the ADC by the scrambling technique has been a research hotspot. From the published literature, no one has applied the scrambling technique to the acquisition of signals by magnetic resonance.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method for enhancing the dynamic range of a magnetic resonance signal by a scrambling technology, wherein a noise interference source is applied to be mixed into a receiving signal of a magnetic resonance signal acquisition unit, distortion harmonic components caused by coherent sampling and quantization errors in the sampling and quantization process of an analog-to-digital converter are reduced, and the spurious-free dynamic range of the magnetic resonance analog-to-digital converter is improved, so that the dynamic range of the magnetic resonance signal is improved.
The purpose of the invention is realized by the following technical scheme: a method for increasing the dynamic range of a magnetic resonance signal by scrambling, comprising the steps of:
s1, adding noise scrambling sources distributed in the m 1-m 2MHz interval at the signal input end of the magnetic resonance signal acquisition board, wherein the amplitude of the noise scrambling sources is n LSBs; wherein m2-m1 is 1, and m2 ranges from 3 to 10; LSB is the lowest bit quantized signal size of the analog-to-digital converter used by the magnetic resonance signal acquisition board, and the value range of n is 5-15;
s2, performing analog-to-digital conversion on the magnetic resonance signal mixed with the noise scrambling source obtained in the step S1;
s3, acquiring a signal at the signal output end of the magnetic resonance signal acquisition board and inputting the signal into a notch filter, and removing extra frequency spectrum components introduced by a noise scrambling source through the notch filter, wherein the stop band range of the notch filter is m 1-m 2 MHz;
and S4, sending the digital signal without the noise scrambling source frequency spectrum to a digital down-conversion processor, and carrying out quadrature demodulation and decimation filtering on the input signal by the digital down-conversion processor.
Further, the noise is white gaussian noise.
Further, the design method of the notch filter comprises the following steps:
s31, determining the performance index of the notch filter: the cut-off frequency of the pass band is (m1-1) MHz and (m2+1) MHz respectively, the cut-off frequency of the stop band is mr1MHz and mr2MHz respectively, and the minimum attenuation of the stop band is alphasMaximum attenuation of passband αp(ii) a Wherein m2-m1 is 1, and m2 ranges from 3 to 10; mr 1-m 1-0.8, mr 2-m 2+ 0.8;
s32, based on the simulation low pass as the design prototype, the band-stop filter designed in the step S31 is digitalized by a bilinear transformation method.
Furthermore, in the digital down-conversion processor, the value range of an extraction factor R of the CIC filter is 20-128000, and the FIR compensation filter performs extraction processing at a fixed extraction rate of 4 times; the single sideband bandwidth BWss of a filter unit consisting of the CIC filter and the FIR compensation filter R is (Fs/R) 0.06875, and the coefficient order of the FIR compensation filter is between 101 and 121; the data width of the data output by the digital down-conversion processor and transmitted to the next-stage processing unit has 2 modes: 16bit or 21 bit; for fast scan, 16bit mode is selected; for application scenarios with high signal-to-noise ratio, the 21bit mode is selected.
The invention has the beneficial effects that: according to the invention, a noise interference source is applied to be mixed into a receiving signal of the magnetic resonance signal acquisition unit, noise scrambling reduces distortion harmonic components of the analog-to-digital converter caused by coherent sampling and quantization errors in the sampling and quantization process, and the energy of the distortion harmonic components is dispersed into a noise substrate, so that the stray-free dynamic range of the magnetic resonance analog-to-digital converter is improved, and the dynamic range of the magnetic resonance signal is further improved; and the frequency spectrum of the noise interference source is far away from the frequency band of the magnetic resonance useful signal in the frequency domain space, and does not generate interference on the magnetic resonance signal.
Drawings
FIG. 1 is a process of the present invention for enhancing the dynamic range of magnetic resonance signals by scrambling techniques;
fig. 2 is a schematic diagram of a digital down-conversion structure.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
As shown in figure 1, the method for enhancing the dynamic range of the magnetic resonance signal by the scrambling technology comprises two parts of noise scrambling and noise descrambling, wherein the noise scrambling comprises the following steps:
s1, adding noise scrambling sources distributed in the m 1-m 2MHz interval at the signal input end of the magnetic resonance signal acquisition board, wherein the amplitude of the noise scrambling sources is n LSBs; wherein m2-m1 is 1, and m2 ranges from 3 to 10; LSB is the lowest bit quantized signal size of the analog-to-digital converter used by the magnetic resonance signal acquisition board, and the value range of n is 5-15;
s2, performing analog-to-digital conversion on the magnetic resonance signal mixed with the noise scrambling source obtained in the step S1;
s3, acquiring a signal at the signal output end of the magnetic resonance signal acquisition board and inputting the signal into a notch filter, and removing extra frequency spectrum components introduced by a noise scrambling source through the notch filter, wherein the stop band range of the notch filter is m 1-m 2 MHz;
the design method of the notch filter comprises the following steps:
s31, determining the performance index of the notch filter: the cut-off frequency of the pass band is (m1-1) MHz and (m2+1) MHz respectively, the cut-off frequency of the stop band is mr1MHz and mr2MHz respectively, and the minimum attenuation of the stop band is alphasMaximum attenuation of passband αp(ii) a Wherein m2-m1 is 1, and m2 ranges from 3 to 10; mr 1-m 1-0.8, mr 2-m 2+ 0.8;
αstypically set to 60dBc, alphapTypically set to 1 dBc;
since the frequency index determined in S31 is an analog frequency, it is necessary to digitize the frequency index at S32. As the design theory of analog filters is mature, the key of digital filter design is to convert h (S) into the corresponding h (Z), i.e. to map the S plane to the Z plane. The method for mapping the S plane to the Z plane comprises the following steps: an impulse response invariant method, a bilinear transformation method, and the like. The invention relies on analog low-pass as the design prototype, and utilizes bilinear transformation method to digitize the band-stop filter designed in step S31. The basic idea of bilinear transformation is to use the difference equation characterizing the digital filter h (z) as an approximate solution to the differential equation corresponding to the analog filter h(s). All occurrences in transfer function h(s) are replaced by Z:
s4, sending the digital signal without the noise scrambling source frequency spectrum to a digital down-conversion processor, and carrying out quadrature demodulation and decimation filtering on the input signal by the digital down-conversion processing; as shown in fig. 2, after the notch filter, quadrature demodulation processing is performed on the signals in the magnetic resonance effective frequency band, and the magnetic resonance complex signals are decomposed into two paths of data, namely a real part and an imaginary part. The data spectrum after quadrature demodulation contains harmonic interference frequency components, so filtering and removing are required to be carried out on a post-stage CIC and FIR compensation filter. The sampling rate of ADC (analog-to-digital conversion) is Fs, if the ADC is directly transmitted according to the rate and is directly transmitted to a post-stage processing unit without extraction processing, the post-stage congestion is caused due to too large data volume, therefore, a CIC filter is designed after an orthogonal demodulation link and is used for extracting large rate, the value range of an extraction factor R of the CIC filter is 20-128000, and R is used for dynamically adjusting the data rate output by CIC; the FIR compensation filter performs decimation processing at a fixed decimation rate of 4 times. The bandwidth BWss of a single sideband of a filter unit consisting of the CIC filter and the FIR compensation filter R is (Fs/R) × 0.06875; the coefficient order of the FIR compensation filter is between 101 and 121; generally, the higher the order, the narrower the transition band of the filter, and the more ideal the frequency response characteristic of the FIR low-pass filter, the more thorough the removal of the scrambling noise and harmonic components which are wrapped to the vicinity of the effective signal frequency band can be achieved; however, the higher the filter order is, the larger the chip logic resource and data delay are required, which affects the speed of reconstructing imaging, so that the setting of the FIR order needs to be determined by comprehensively considering the two factors. The data width of data output by a DDC (digital down-conversion processor) and transmitted to a next-stage processing unit has 2 modes: 16bit or 21 bit. For fast scanning, a 16bit mode is usually selected due to the high data rate throughput; for the application scenario with high signal-to-noise ratio, the loss of signal accuracy needs to be reduced as much as possible, and a 21-bit mode is usually selected. The FIFO exists as a data buffer link between the DDC and the next-level processing unit.
Further, the noise is white gaussian noise.
Coherent sampling means that the sampling frequency and the frequency of an input signal are in integral multiple relation, and the quantization error is inevitably distributed in a periodic performance manner due to the coherent sampling. As can be seen from the definition of coherent sampling, coherent sampling only occurs when the input signal is a single frequency signal. Any signal can be viewed as a combination of one or more single-frequency components, so for a sampling frequency there will always be one or more single-frequency components with which to form coherent samples. During the actual sampling, coherent sampling is almost inevitable, and harmonics formed by the coherent sampling are also inevitable. The SFDR degradation caused by coherent sampling can be eliminated by the noise scrambling source added by the present invention.
The influence of DNL periodicity on quantization error can also be understood from the perspective of the transfer function of a pipelined ADC, which can be deduced from the quantization characteristics of the ADC, and the transfer function of an ideal ADC can be expressed as:
wherein X is formed by [ (n-1) LSB, nLSB ]
For a non-ideal ADC, the transfer function can be expressed as:
wherein the content of the first and second substances,
as can be seen from equation (2), since the DNL of the pipelined ADC has periodicity, its transfer function must also have periodicity. Harmonics resulting from the periodicity of the transfer function can be improved with diter. For example, when the period of the transfer function takes n LSBs as a cycle, as long as the mean square value (RMS) of the introduced diter is greater than n LSBs, the period of the transfer function may be skipped by the total level of the signal plus the diter due to the influence of the diter, and the input signal plus the diter is not affected by the periodicity of the transfer function because the diter is random with respect to the input signal, that is, the input signal is not affected by the periodicity of the transfer function any more (the diter is filtered and removed at the digital end).
Since the signal of the magnetic resonance is a narrow-band signal, in the 3T magnetic resonance system, the distribution range of the useful signal is 127.21MHz to 128.21 MHz. The distribution range of the added noise scrambling signals is 2MHz to 9MHz, the frequency spectrum of a noise interference source is far away from the frequency band of the magnetic resonance useful signals in the frequency domain space, and the interference to the magnetic resonance signals can not be generated. The noise scrambling reduces distortion harmonic components caused by coherent sampling and quantization errors in the sampling and quantization process of the analog-to-digital converter, disperses the energy of the distortion harmonic components into a noise substrate, and improves the spurious-free dynamic range of the magnetic resonance analog-to-digital converter, thereby improving the dynamic range of magnetic resonance signals.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art can make various other specific changes and combinations based on the teachings of the present invention without departing from the spirit of the invention, and these changes and combinations are within the scope of the invention.
Claims (2)
1. A method for enhancing the dynamic range of a magnetic resonance signal by scrambling, comprising the steps of:
s1, adding noise scrambling sources distributed in the m 1-m 2MHz interval at the signal input end of the magnetic resonance signal acquisition board, wherein the amplitude of the noise scrambling sources is n LSBs; wherein m2-m1 is 1, and m2 ranges from 3 to 10; LSB is the lowest bit quantized signal size of the analog-to-digital converter used by the magnetic resonance signal acquisition board, and the value range of n is 5-15;
s2, performing analog-to-digital conversion on the magnetic resonance signal mixed with the noise scrambling source obtained in the step S1;
s3, acquiring a signal at the signal output end of the magnetic resonance signal acquisition board and inputting the signal into a notch filter, and removing extra frequency spectrum components introduced by a noise scrambling source through the notch filter, wherein the stop band range of the notch filter is m 1-m 2 MHz; the design method of the notch filter comprises the following steps:
s31, determining the performance index of the notch filter: the cut-off frequency of the pass band is (m1-1) MHz and (m2+1) MHz respectively, the cut-off frequency of the stop band is mr1MHz and mr2MHz respectively, and the minimum attenuation of the stop band is alphasMaximum attenuation of passband αp(ii) a Wherein m2-m1 is 1, and m2 ranges from 3 to 10; mr 1-m 1-0.8, mr 2-m 2+ 0.8;
s32, based on the analog low pass as a design prototype, digitizing the band-stop filter designed in the step S31 by using a bilinear transformation method;
s4, sending the digital signal without the noise scrambling source frequency spectrum to a digital down-conversion processor, and carrying out quadrature demodulation and decimation filtering on the input signal by the digital down-conversion processing; in the digital down-conversion processor, the value range of an extraction factor R of a CIC filter is 20-128000, and an FIR compensation filter performs extraction processing at a fixed extraction rate of 4 times; the single sideband bandwidth BWss of a filter unit consisting of the CIC filter and the FIR compensation filter R is (Fs/R) 0.06875, wherein Fs represents the sampling rate of the analog-digital converter; the coefficient order of the FIR compensation filter is between 101 and 121; the data width of the data output by the digital down-conversion processor and transmitted to the next-stage processing unit has 2 modes: 16bit or 21 bit; for fast scan, 16bit mode is selected; for application scenarios with high signal-to-noise ratio, the 21bit mode is selected.
2. The method for enhancing the dynamic range of a magnetic resonance signal by scrambling technique as claimed in claim 1, wherein the noise is white gaussian noise.
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