WO2019119506A1 - 磁共振温度成像方法与装置 - Google Patents

磁共振温度成像方法与装置 Download PDF

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WO2019119506A1
WO2019119506A1 PCT/CN2017/119483 CN2017119483W WO2019119506A1 WO 2019119506 A1 WO2019119506 A1 WO 2019119506A1 CN 2017119483 W CN2017119483 W CN 2017119483W WO 2019119506 A1 WO2019119506 A1 WO 2019119506A1
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signal
water
fat
relaxation time
intensity
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PCT/CN2017/119483
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English (en)
French (fr)
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郑海荣
刘新
邹超
程传力
乔阳紫
帖长军
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深圳先进技术研究院
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Priority to EP17935744.7A priority Critical patent/EP3730046A4/en
Publication of WO2019119506A1 publication Critical patent/WO2019119506A1/zh
Priority to US16/888,882 priority patent/US20200292651A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G01R33/4804—Spatially selective measurement of temperature or pH
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
    • A61B5/015—By temperature mapping of body part
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G01R33/50—NMR imaging systems based on the determination of relaxation times, e.g. T1 measurement by IR sequences; T2 measurement by multiple-echo sequences
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G01R33/4828—Resolving the MR signals of different chemical species, e.g. water-fat imaging

Definitions

  • the present invention relates to the field of magnetic resonance, and in particular to a magnetic resonance temperature imaging method and apparatus.
  • Magnetic resonance temperature imaging can monitor the internal temperature distribution and changes of the test object in a non-invasive, real-time and in-vivo manner. Magnetic resonance can monitor temperature based on different temperature sensitive parameters. Probological parameters include proton density (PD), relaxation time, diffusion coefficient, and proton resonance frequency shift (PRFS). . Because the proton resonance frequency in water is linear with temperature, and the linear relationship is independent of tissue, PRFS-based magnetic resonance temperature imaging technology is the most widely used. However, this technique cannot be applied to tissues containing fat, so the hydrogen protons in fat are not sensitive to temperature, which makes the lipid-containing structure have a nonlinear relationship with temperature changes, and this nonlinear relationship is related to the ratio of water and fat in the tissue. . In order to achieve temperature imaging of adipose tissue, the effects of fat need to be eliminated or corrected.
  • PD proton density
  • PRFS proton resonance frequency shift
  • an embodiment of the present invention provides a magnetic resonance temperature imaging method, where the magnetic resonance temperature imaging method includes:
  • the pre-assigned initial water-fat tissue temperature image and the water-lipid separation algorithm the first intensity amplitude of the water signal, the first phase value of the water signal, the first intensity amplitude of the fat signal, and the fat are obtained.
  • the first intensity amplitude of the water signal, the first phase value of the water signal, the first intensity amplitude of the fat signal, the first phase value of the fat signal, the first transverse relaxation time of the water, and the first fat is first fitted to the pre-set magnetic resonance signal model, and the difference between the signal intensity after the first fitting and the signal intensity before the fitting is obtained.
  • the second transverse relaxation time of water, the second transverse relaxation time of fat, and the second field drift caused by the unevenness of the main magnetic field are second fitted to a pre-set magnetic resonance signal model, obtained after the second fitting.
  • the third intensity amplitude of the water signal with the smallest difference between the signal strength and the signal intensity before fitting, the third phase value of the water signal, the third intensity amplitude of the fat signal, the third phase value of the fat signal, and the third transverse relaxation of water The third transverse relaxation time caused by the time, the third transverse relaxation time of the fat and the uneven main magnetic field;
  • the field is fitted to the pre-set magnetic resonance signal model for the third time, and the fourth intensity amplitude and fat signal fourth are obtained, which minimizes the difference between the signal intensity after the third fitting and the signal intensity before fitting.
  • the amplitude of the intensity, the fourth field drift caused by the uneven main magnetic field, and the temperature profile of the water-fat tissue at the current moment.
  • an embodiment of the present invention further provides a magnetic resonance temperature imaging apparatus, where the magnetic resonance temperature imaging apparatus includes:
  • the first calculating unit is configured to obtain a first intensity amplitude of the water signal, a first phase value of the water signal, and a fat signal according to the preset magnetic resonance signal model, the pre-assigned initial water-fat tissue temperature image, and the water-lipid separation algorithm.
  • a second calculating unit configured to determine an initial water-fat tissue temperature image, a first intensity amplitude of the water signal, a first phase value of the water signal, a first intensity magnitude of the fat signal, a first phase value of the fat signal, and a first lateral direction of the water
  • the relaxation time, the first transverse relaxation time of the fat, and the first field drift caused by the inhomogeneity of the main magnetic field are first fitted to the pre-set magnetic resonance signal model, and the signal intensity after the first fitting is obtained.
  • a third calculating unit configured to maintain the second water-fat tissue temperature image unchanged, according to the second water-fat tissue temperature image, the second intensity amplitude of the water signal, the second phase value of the water signal, the second intensity amplitude of the fat signal, The second phase value of the fat signal, the second transverse relaxation time of the water, the second transverse relaxation time of the fat, and the second field-floating second-time fitting of the pre-set magnetic resonance signal model caused by the unevenness of the main magnetic field are obtained.
  • the third intensity amplitude of the water signal, the third phase value of the water signal, the third intensity amplitude of the fat signal, and the third phase value of the fat signal which minimize the difference between the signal intensity after the second fitting and the signal intensity before fitting
  • a fourth calculating unit configured to maintain a third phase value of the water signal, a third phase value of the fat signal, a third transverse relaxation time of the water, and a third transverse relaxation time of the fat, according to the second water lipid tissue temperature image
  • the third field drift caused by the non-uniform magnetic field performs a third fitting on the pre-set magnetic resonance signal model, and obtains the water signal that minimizes the difference between the signal intensity after the third fitting and the signal intensity before fitting.
  • the magnetic resonance temperature imaging method and device improve the accuracy and accuracy of the current temperature profile of the water-fat tissue by the two-step iterative temperature estimation algorithm, and the magnetic resonance signal model includes The fat is multi-peak, and the fourth intensity amplitude of the water signal with the smallest difference between the signal intensity and the signal intensity before fitting, the fourth intensity amplitude of the fat signal, the fourth field drift caused by the uneven main magnetic field, and the current moment are estimated.
  • the temperature profile of the water-fat tissue ensures unbiased temperature results.
  • FIG. 1 is a structural block diagram of a server provided by the present invention.
  • FIG. 2 is a flow chart of a magnetic resonance temperature imaging method provided by the present invention.
  • FIG. 3 is a block diagram showing the functional structure of a magnetic resonance temperature imaging apparatus provided by the present invention.
  • Icon 100-magnetic resonance temperature imaging device; 200-server; 101-memory; 102-storage controller; 103-processor; 104-peripheral interface; 301-first computing unit; 302-second computing unit; a third calculation unit; 304-filter unit; 305-fourth calculation unit.
  • FIG. 1 is a block diagram showing the structure of a server 200 in an embodiment of the present invention.
  • the server 200 includes a magnetic resonance temperature imaging apparatus 100, a memory 101, a memory controller 102, one or more (only one shown) processor 103, a peripheral interface 104, and the like. These components communicate with one another via one or more communication bus/signal lines.
  • the magnetic resonance temperature imaging apparatus 100 includes at least one software function module that can be stored in the memory 101 or in an operating system (OS) of the server 200 in the form of software or firmware.
  • OS operating system
  • the memory 101 can be used to store software programs and modules, such as program instructions/modules corresponding to the image processing apparatus and method in the embodiment of the present invention.
  • the processor 103 executes various programs by running software programs and modules stored in the memory 101. Functional application and data processing, such as the magnetic resonance temperature imaging method provided by the embodiments of the present invention.
  • Memory 101 can include high speed random access memory and can also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid state memory. Access to the memory 101 by the processor 103 and other possible components can be performed under the control of the memory controller 102.
  • Peripheral interface 104 couples various input/output devices to processor 103 and memory 101.
  • peripheral interface 104, processor 103, and memory controller 102 can be implemented in a single chip. In other instances, they can be implemented by separate chips.
  • FIG. 1 is merely illustrative, and the server 200 may further include more or less components than those shown in FIG. 1, or have a different configuration than that shown in FIG.
  • the components shown in Figure 1 can be implemented in hardware, software, or a combination thereof.
  • an embodiment of the present invention provides a magnetic resonance temperature imaging method, where the magnetic resonance temperature imaging method includes:
  • Step S201 obtaining a first intensity amplitude of the water signal, a first phase value of the water signal, and a first intensity amplitude of the fat signal according to the preset magnetic resonance signal model, the pre-assigned initial water-fat tissue temperature image, and the water-lipid separation algorithm.
  • the preset magnetic resonance signal model is Wherein, S n is the signal strength at the echo time TE n; W is water signal strength value, F is the fat signal strength value, ⁇ is the gyromagnetic ratio, B 0 magnetic field intensity based, ⁇ is the temperature coefficient of the water proton , P is the number of fat peaks, and the corresponding relative amplitude and chemical shift are ⁇ p and f F,p , respectively.
  • S n is the signal strength at the echo time TE n
  • W water signal strength value
  • F the fat signal strength value
  • ⁇ the gyromagnetic ratio
  • B 0 magnetic field intensity based ⁇
  • ⁇ the temperature coefficient of the water proton
  • P is the number of fat peaks
  • the corresponding relative amplitude and chemical shift are ⁇ p and f F,p , respectively.
  • N is the total number of echoes collected
  • ⁇ T is the temperature profile of the water-fat tissue.
  • Step S202 According to the initial water lipid tissue temperature image, the first intensity amplitude of the water signal, the first phase value of the water signal, the first intensity amplitude of the fat signal, the first phase value of the fat signal, the first transverse relaxation time of the water, The first transverse relaxation time of the fat and the first field drift caused by the non-uniform magnetic field are first fitted to the pre-set magnetic resonance signal model, and the signal intensity after the first fitting and the signal before the fitting are obtained.
  • the second intensity amplitude of the water signal with the smallest intensity difference, the second phase value of the fat signal, the second intensity amplitude of the fat signal, the second phase value of the water signal, the second transverse relaxation time of the water, and the second transverse relaxation of the fat The second field and the second water-fat tissue temperature image caused by the uneven time of the main magnetic field.
  • the pre-set magnetic resonance signal model is fitted for the first time.
  • Step S203 Smoothing the second water-fat tissue temperature image with a low-pass filter to obtain a smoothed second water-fat tissue temperature image.
  • the second water-fat tissue temperature image is smoothed by a low-pass filter to obtain a smoothed second water-fat tissue temperature image, wherein ⁇ T i is the current temperature estimation value of the ith pixel. For the mean of all pixel temperature values, The temperature value after smoothing the i-th pixel.
  • Step S204 maintaining the second water-fat tissue temperature image after the smoothing process is unchanged, according to the second water-fat tissue temperature image, the second intensity amplitude of the water signal, the second phase value of the water signal, the second intensity amplitude of the fat signal, The second phase value of the fat signal, the second transverse relaxation time of the water, the second transverse relaxation time of the fat, and the second field-floating second-time fitting of the pre-set magnetic resonance signal model caused by the unevenness of the main magnetic field are obtained.
  • the third intensity amplitude of the water signal, the third phase value of the water signal, the third intensity amplitude of the fat signal, and the third phase value of the fat signal which minimize the difference between the signal intensity after the second fitting and the signal intensity before fitting.
  • the second set of pre-set magnetic resonance signal models is fitted.
  • Step S205 maintaining the third phase value of the water signal, the third phase value of the fat signal, the third transverse relaxation time of the water, and the third transverse relaxation time of the fat, according to the second water lipid tissue temperature image and the water signal number
  • the third field is fitted to the pre-set magnetic resonance signal model for the third time, and the fourth intensity amplitude and fat of the water signal which minimizes the difference between the signal intensity after the third fitting and the signal intensity before the fitting is obtained.
  • the fourth intensity amplitude of the signal, the fourth field drift caused by the uneven main magnetic field, and the temperature profile of the water lipid tissue at the current moment.
  • the pre-set magnetic resonance signal model is fitted for the third time.
  • the magnetic resonance temperature imaging method firstly obtains a second intensity amplitude of the water signal, a second phase value of the water signal, and a water signal by minimizing the difference between the signal intensity and the signal intensity before the fitting by fitting the preset magnetic resonance signal model.
  • the second intensity amplitude, the second phase value of the water signal, the second transverse relaxation time of the water, the second transverse relaxation time of the fat, the second field drift caused by the uneven main magnetic field, and the second water lipid tissue temperature image are guaranteed
  • the temperature estimation is not biased, that is, the accuracy of the second water-fat tissue temperature image is ensured; then the second water-fat tissue temperature image is smoothed, and the signal intensity after the second fitting is obtained.
  • the third intensity amplitude of the water signal with the smallest difference in signal intensity, the third phase value of the water signal, the third intensity amplitude of the water signal, the third phase value of the water signal, the third transverse relaxation time of water, fat The third transverse relaxation time and the third field drift caused by the non-uniform magnetic field are re-estimated, at which time the third phase value of the water signal, the third phase value of the fat signal, the third transverse relaxation time of the water, and the fat are obtained.
  • the third transverse relaxation time is accurate; finally the third phase value of the fixed water signal, the third phase value of the fat signal, the third transverse relaxation time of the water, and the third transverse relaxation time of the fat, re-fitting the signal model Obtaining the fourth intensity amplitude, the fourth intensity amplitude of the fat signal, the fourth field drift caused by the uneven main magnetic field, and the current temperature profile of the water lipid tissue, since the free variables in the preset magnetic resonance signal model are reduced The accuracy of the resulting pre-set magnetic resonance signal model is improved.
  • the water-fat tissue temperature image of the current time can be obtained by repeating the above steps S201 to S205 by using the initial water-fat tissue temperature image as the initial value of the next cycle, and the water-fat tissue temperature image at the next time can be obtained.
  • an embodiment of the present invention further provides a magnetic resonance temperature imaging apparatus 100.
  • the magnetic resonance temperature imaging apparatus 100 includes a first calculation unit 301, a second calculation unit 302, a third calculation unit 303, a filtering unit 304, and a fourth calculation unit 305.
  • the first calculating unit 301 is configured to obtain a first intensity amplitude of the water signal, a first phase value of the water signal, and a fat signal according to the preset magnetic resonance signal model, the pre-assigned initial water lipid tissue temperature image, and the water and lipid separation algorithm.
  • the preset magnetic resonance signal model is wherein, S n is the signal strength at the echo time TE n; W is water signal strength value, F is the fat signal strength value, ⁇ is the gyromagnetic ratio, B 0 magnetic field intensity based, ⁇ is the temperature coefficient of the water proton , P is the number of fat peaks, and the corresponding relative amplitude and chemical shift are ⁇ p and f F,p , respectively.
  • f b is the field drift due to the non-uniform main magnetic field
  • N is the total number of echoes collected
  • ⁇ T is the temperature profile of the water-fat tissue.
  • the first calculating unit 301 can perform step S201.
  • the second calculating unit 302 is configured to be based on the initial water-fat tissue temperature image, the first intensity amplitude of the water signal, the first phase value of the water signal, the first intensity amplitude of the fat signal, the first phase value of the fat signal, and the first lateral direction of the water.
  • the relaxation time, the first transverse relaxation time of the fat, and the first field drift caused by the inhomogeneity of the main magnetic field are first fitted to the pre-set magnetic resonance signal model, and the signal intensity after the first fitting is obtained.
  • the second intensity amplitude of the water signal with the smallest difference in signal intensity, the second phase value of the water signal, the second intensity amplitude of the water signal, the second phase value of the water signal, the second transverse relaxation time of the water, the fat The second transverse relaxation time, the second field drift caused by the uneven main magnetic field, and the second water lipid tissue temperature image.
  • the second calculating unit 302 is configured to use the formula
  • the pre-set magnetic resonance signal model is fitted for the first time.
  • the second calculating unit 302 can perform step S202.
  • the filtering unit 304 is configured to perform a smoothing process on the second water-fat tissue temperature image using a low-pass filter to obtain a smoothed second water-fat tissue temperature image.
  • the filtering unit 304 can perform step S203.
  • the filtering unit 304 is configured to use a formula
  • the second water-fat tissue temperature image is smoothed by a low-pass filter to obtain a smoothed second water-fat tissue temperature image, wherein ⁇ T i is the current temperature estimation value of the ith pixel. For the mean of all pixel temperature values, The temperature value after smoothing the i-th pixel.
  • the third calculating unit 303 is configured to keep the second water-fat tissue temperature image unchanged, according to the second water-fat tissue temperature image, the second intensity amplitude of the water signal, the second phase value of the water signal, the second intensity amplitude of the fat signal, The second phase value of the fat signal, the second transverse relaxation time of the water, the second transverse relaxation time of the fat, and the second field-floating second-time fitting of the pre-set magnetic resonance signal model caused by the unevenness of the main magnetic field are obtained.
  • the third intensity amplitude of the water signal, the third phase value of the fat signal, the third intensity amplitude of the fat signal, and the third phase value of the water signal which minimize the difference between the signal intensity after the second fitting and the signal intensity before fitting.
  • the third calculating unit 303 is configured to follow the formula
  • the second set of pre-set magnetic resonance signal models is fitted.
  • the third calculating unit 303 can perform step S204.
  • the fourth calculating unit 305 is configured to maintain the water signal third phase value, the fat signal third phase value, the third transverse relaxation time of the water, and the third transverse relaxation time of the fat, according to the second water lipid tissue temperature image.
  • the third field drift caused by the non-uniform magnetic field performs a third fitting on the pre-set magnetic resonance signal model, and obtains the water signal that minimizes the difference between the signal intensity after the third fitting and the signal intensity before fitting.
  • the fourth calculating unit 305 is configured to depend on the formula
  • the pre-set magnetic resonance signal model is fitted for the third time.
  • the fourth calculating unit 305 can perform step S205.
  • the magnetic resonance temperature imaging method and apparatus improve the accuracy and accuracy of the current temperature profile of the water-fat tissue by a two-step iterative temperature estimation algorithm.
  • the magnetic resonance signal model contains fat multi-peak and is estimated at the same time.
  • the fourth intensity amplitude of the water signal with the smallest difference between the signal intensity and the signal intensity before fitting, the fourth intensity amplitude of the fat signal, the fourth field drift caused by the uneven main magnetic field, and the temperature profile of the water lipid tissue at the current moment are obtained. To ensure the unbiased temperature results.
  • each block of the flowchart or block diagram can represent a module, a program segment, or a portion of code that includes one or more of the Executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the blocks may also occur in a different order than those illustrated in the drawings.
  • each block of the block diagrams and/or flowcharts, and combinations of blocks in the block diagrams and/or flowcharts can be implemented in a dedicated hardware-based system that performs the specified function or function. Or it can be implemented by a combination of dedicated hardware and computer instructions.
  • each functional module in each embodiment of the present invention may be integrated to form a separate part, or each module may exist separately, or two or more modules may be integrated to form a separate part.
  • the functions, if implemented in the form of software functional modules and sold or used as separate products, may be stored in a computer readable storage medium.
  • the technical solution of the present invention which is essential or contributes to the prior art, or a part of the technical solution, may be embodied in the form of a software product, which is stored in a storage medium, including
  • the instructions are used to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .

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Abstract

本发明提供了一种磁共振温度成像方法与装置，涉及磁共振领域。该磁共振温度成像方法与装置通过两步迭代温度估计的算法提高了当前时刻的水脂组织温度图像的准确度和精确度，磁共振信号模型包含有脂肪多峰，同时估计得到了信号强度与拟合前的信号强度差值最小的水信号第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像，保证了温度结果的无偏性。

Description

磁共振温度成像方法与装置
相关申请的交叉引用
本申请要求于2017年12月20日提交中国专利局的申请号为201711387804.1、名称为“磁共振温度成像方法与装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明涉及磁共振领域，具体而言，涉及一种磁共振温度成像方法与装置。
背景技术
磁共振温度成像可以无创、实时且在体地监测被试物体内部温度分布及变化。磁共振可基于不同的温度敏感参数对温度进行监测，常用的参数有质子浓度(proton density，PD)、弛豫时间(relaxation time)、扩散系数和质子共振频率漂移(proton resonance frequency shift，PRFS)。因为水中的质子共振频率和温度成线性关系，且该线性关系和组织无关，因此基于PRFS的磁共振温度成像技术应用最为广泛。但是该技术不能用于含有脂肪的组织，因此脂肪中的氢质子对温度不敏感，这就使得含脂组织与温度变化呈现非线性关系，且此非线性关系与组织中水和脂肪的比例有关。为了实现对含有脂肪组织的温度成像，需对脂肪的影响进行消除或校正。
发明内容
有鉴于此，本发明实施例的目的在于提供一种磁共振温度成像方法与装置，以改善上述的问题。
第一方面，本发明实施例提供了一种磁共振温度成像方法，所述磁共振温度成像方法包括：
依据预设定的磁共振信号模型、预先赋予的初始水脂组织温度图像以及水脂分离算法，获得水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘；
依据初始水脂组织温度图像、水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘第一次拟合预设定的磁共振信号模型，获得使得第一次拟合后的信号强度与拟合前的信号强度差值最小的水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间、主磁场不均匀造成的第二场飘和第二水脂组织温度图像；
保持第二水脂组织温度图像不变，依据第二水脂组织温度图像、水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间和主磁场不均匀造成的第二场飘第二次拟合预设定的磁共振信号模型，获得使得第二次拟合后的信号强度与拟合前的信号强度差值最小的水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘；
保持水信号第三相位值、脂肪信号第三相位值、水的第三横向弛豫时间和脂肪的第三横向弛豫时间不变，依据第二水脂组织温度图像、水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘第三次拟合预设定的磁共振信号模型，获得使得第三次拟合后的信号强度与拟合前的信号强度差值最小的水信号第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像。
第二方面，本发明实施例还提供了一种磁共振温度成像装置，所述磁共振温度成像装置包括：
第一计算单元，配置成依据预设定的磁共振信号模型、预先赋予的初始水脂组织温度图像以及水脂分离算法，获得水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘；
第二计算单元，配置成依据初始水脂组织温度图像、水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘第一次拟合预设定的磁共振信号模型，获得使得第一次拟合后的信号强度与拟合前的信号强度差值最小的水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间、主磁场不均匀造成的第二场飘和第二水脂组织温度图像；
第三计算单元，配置成保持第二水脂组织温度图像不变，依据第二水脂组织温度图像、水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间和主磁场不均匀造成的第二场飘第二次拟合预设定的磁共振信号模型，获得使得第二次拟合后的信号强度与拟合前的信号强度差值最小的水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘；
第四计算单元，配置成保持水信号第三相位值、脂肪信号第三相位值、水的第三横向弛豫时间和脂肪的第三横向弛豫时间不变，依据第二水脂组织温度图像、水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘对预设定的磁共振信号模型进行第三次拟合，获得使得第三次拟合后的信号强度与拟合前的信号强度差值最小的水信号第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像。
与现有技术相比，本发明提供的磁共振温度成像方法与装置，通过两步迭代温度估计的算法提高了当前时刻的水脂组织温度图像的准确度和精确度，磁共振信号模型包含有脂肪多峰，同时估计得到了信号强度与拟合前的信号强度差值最小的水信号第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像，保证了温度结果的无偏性。
为使本发明的上述目的、特征和优点能更明显易懂，下文特举较佳实施例，并配合所附附图，作详细说明如下。
附图说明
为使本发明实施例的目的、技术方案和优点更加清楚，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。通常在此处附图中描述和示出的本发明实施例的组件可以以各种不同的配置来布置和设计。因此，以下对在附图中提供的本发明的实施例的详细描述并非旨在限制要求保护的本发明的范围，而是仅仅表示本发明的选定实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
图1为本发明提供的服务器的结构框图；
图2为本发明提供的磁共振温度成像方法的流程图；
图3为本发明提供的磁共振温度成像装置的功能结构框图。
图标：100-磁共振温度成像装置；200-服务器；101-存储器；102-存储控制器；103-处理器；104-外设接口；301-第一计算单元；302-第二计算单元；303-第三计算单元；304-滤波单元；305-第四计算单元。
具体实施方式
下面将结合本发明实施例中附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。通常在此处附图中描述和示出的本发明实施例的组件可以以各种不同的配置来布置和设计。因此， 以下对在附图中提供的本发明的实施例的详细描述并非旨在限制要求保护的本发明的范围，而是仅仅表示本发明的选定实施例。基于本发明的实施例，本领域技术人员在没有做出创造性劳动的前提下所获得的所有其他实施例，都属于本发明保护的范围。
本发明较佳实施例所提供的磁共振温度成像方法与装置可应用于服务器200。图1示出了本发明实施例中的服务器200的结构框图。如图1所示，服务器200包括磁共振温度成像装置100、存储器101、存储控制器102，一个或多个(图中仅示出一个)处理器103、外设接口104等。这些组件通过一条或多条通讯总线/信号线相互通讯。所述磁共振温度成像装置100包括至少一个可以软件或固件(firmware)的形式存储于所述存储器101中或固化在所述服务器200的操作***(operating system，OS)中的软件功能模块。
存储器101可用于存储软件程序以及模块，如本发明实施例中的图片处理装置及方法所对应的程序指令/模块，处理器103通过运行存储在存储器101内的软件程序以及模块，从而执行各种功能应用以及数据处理，如本发明实施例提供的磁共振温度成像方法。存储器101可包括高速随机存储器，还可包括非易失性存储器，如一个或者多个磁性存储装置、闪存、或者其他非易失性固态存储器。处理器103以及其他可能的组件对存储器101的访问可在存储控制器102的控制下进行。
外设接口104将各种输入/输出装置耦合至处理器103以及存储器101。在一些实施例中，外设接口104、处理器103以及存储控制器102可以在单个芯片中实现。在其他一些实例中，他们可以分别由独立的芯片实现。
可以理解，图1所示的结构仅为示意，服务器200还可包括比图1中所示更多或者更少的组件，或者具有与图1所示不同的配置。图1中所示的各组件可以采用硬件、软件或其组合实现。
请参阅图2，本发明实施例提供了一种磁共振温度成像方法，所述磁共振温度成像方法包括：
步骤S201：依据预设定的磁共振信号模型、预先赋予的初始水脂组织温度图像以及水脂分离算法，获得水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘。
具体地，所述预设定的磁共振信号模型为
Figure PCTCN2017119483-appb-000001
其中，S n为在回波时间TE n下的信号强度；W为水信号强度值，F为脂肪信号强度值，γ为 旋磁比，B 0为主磁场强度，α为水中氢质子温度系数，P为脂肪峰的个数，对应的相对幅值和化学位移分别为β p和f F,p，且
Figure PCTCN2017119483-appb-000002
Figure PCTCN2017119483-appb-000003
为水的横向弛豫时间，
Figure PCTCN2017119483-appb-000004
为脂肪的横向弛豫时间，f b为由于主磁场不均匀造成的场飘，N是总共采集回波个数；ΔT为水脂组织温度图像。
步骤S202：依据初始水脂组织温度图像、水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘第一次拟合预设定的磁共振信号模型，获得使得第一次拟合后的信号强度与拟合前的信号强度差值最小的水信号第二强度幅值、脂肪信号第二相位值、脂肪信号第二强度幅值、水信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间、主磁场不均匀造成的第二场飘和第二水脂组织温度图像。
具体地，依据算式
Figure PCTCN2017119483-appb-000005
第一次拟合预设定的磁共振信号模型。
步骤S203：对第二水脂组织温度图像采用低通滤波器进行平滑处理从而获得平滑处理后的第二水脂组织温度图像。
具体地，依据算式
Figure PCTCN2017119483-appb-000006
第二水脂组织温度图像采用低通滤波器进行平滑处理从而获得平滑处理后的第二水脂组织温度图像，其中，ΔT i为第i个像素的当前温度估计值，
Figure PCTCN2017119483-appb-000007
为所有像素点温度值的均值，
Figure PCTCN2017119483-appb-000008
为第i个像素点平滑处理后的温度值。
步骤S204：保持平滑处理后的第二水脂组织温度图像不变，依据第二水脂组织温度图像、水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间和主磁场不均匀造成的第二场飘 第二次拟合预设定的磁共振信号模型，获得使得第二次拟合后的信号强度与拟合前的信号强度差值最小的水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘。
具体地，依据算式
Figure PCTCN2017119483-appb-000009
第二次拟合预设定的磁共振信号模型。
步骤S205：保持水信号第三相位值、脂肪信号第三相位值、水的第三横向弛豫时间和脂肪的第三横向弛豫时间不变，依据第二水脂组织温度图像、水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘第三次拟合预设定的磁共振信号模型，获得使得第三次拟合后的信号强度与拟合前的信号强度差值最小的水信号第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像。
具体地，依据算式
Figure PCTCN2017119483-appb-000010
第三次拟合预设定的磁共振信号模型。
该磁共振温度成像方法首先通过拟合预设定的磁共振信号模型得到信号强度与拟合前的信号强度差值最小的水信号第二强度幅值、水信号第二相位值、水信号第二强度幅值、水信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间、主磁场不均匀造成的第二场飘和第二水脂组织温度图像，保证了温度估计是没有偏差的，即保证了第二水脂组织温度图像的准确度；而后将第二水脂组织温度图像进行平滑处理，并对获得使得第二次拟合后的信号强度与拟合前的信号强度差值最小的水信号第三强度幅值、水信号第三相位值、水信号第三强度幅值、水信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘进行重新估计，这时得到水信号第三相位值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间是准确的；最后固定水信号第三相位值、脂肪信号第三相位值、水的第三横向弛豫时间和脂肪的第三横向 弛豫时间，重新拟合信号模型得到第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像，由于减少了预设定的磁共振信号模型中自由变量的个数，得到的预设定的磁共振信号模型的精确度得到了提高。
另外，可以将当前时刻的水脂组织温度图像，将初始水脂组织温度图像作为下一个循环的初始值，重复上述步骤S201～S205，即可得到下一时刻的水脂组织温度图像。
请参阅图2，本发明实施例还提供了一种磁共振温度成像装置100，需要说明的是，本发明实施例所提供的磁共振温度成像装置100，其基本原理及产生的技术效果和上述实施例相同，为简要描述，本发明实施例部分未提及之处，可参考上述的实施例中相应内容。所述磁共振温度成像装置100包括第一计算单元301、第二计算单元302、第三计算单元303、滤波单元304和第四计算单元305。
第一计算单元301配置成依据预设定的磁共振信号模型、预先赋予的初始水脂组织温度图像以及水脂分离算法，获得水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘。
其中，所述预设定的磁共振信号模型为
Figure PCTCN2017119483-appb-000011
其中，S n为在回波时间TE n下的信号强度；W为水信号强度值，F为脂肪信号强度值，γ为旋磁比，B 0为主磁场强度，α为水中氢质子温度系数，P为脂肪峰的个数，对应的相对幅值和化学位移分别为β p和f F,p，且
Figure PCTCN2017119483-appb-000012
Figure PCTCN2017119483-appb-000013
为水的横向弛豫时间，
Figure PCTCN2017119483-appb-000014
为脂肪的横向弛豫时间，f b为由于主磁场不均匀造成的场飘，N是总共采集回波个数；ΔT为水脂组织温度图像。
可以理解地，第一计算单元301可以执行步骤S201。
第二计算单元302配置成依据初始水脂组织温度图像、水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘第一次拟合预设定的磁共振信号模型，获得使得第一次拟合后的信号强度与拟合前的信号强度差值最小的水信号第二强度幅值、水信号第二相位值、水信号第二强度幅值、水信号第二相位值、水的第二横向弛豫时 间、脂肪的第二横向弛豫时间、主磁场不均匀造成的第二场飘和第二水脂组织温度图像。
所述第二计算单元302用于依据算式
Figure PCTCN2017119483-appb-000015
第一次拟合预设定的磁共振信号模型。
可以理解地，第二计算单元302可以执行步骤S202。
滤波单元304配置成对第二水脂组织温度图像采用低通滤波器进行平滑处理从而获得平滑处理后的第二水脂组织温度图像。
可以理解地，滤波单元304可以执行步骤S203。
所述滤波单元304用于依据算式
Figure PCTCN2017119483-appb-000016
第二水脂组织温度图像采用低通滤波器进行平滑处理从而获得平滑处理后的第二水脂组织温度图像，其中，ΔT i为第i个像素的当前温度估计值，
Figure PCTCN2017119483-appb-000017
为所有像素点温度值的均值，
Figure PCTCN2017119483-appb-000018
为第i个像素点平滑处理后的温度值。
第三计算单元303配置成保持第二水脂组织温度图像不变，依据第二水脂组织温度图像、水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间和主磁场不均匀造成的第二场飘第二次拟合预设定的磁共振信号模型，获得使得第二次拟合后的信号强度与拟合前的信号强度差值最小的水信号第三强度幅值、脂肪信号第三相位值、脂肪信号第三强度幅值、水信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘。
第三计算单元303配置成依据算式
Figure PCTCN2017119483-appb-000019
第二次拟合预设定的磁共振信号模型。
可以理解地，第三计算单元303可以执行步骤S204。
第四计算单元305配置成保持水信号第三相位值、脂肪信号第三相位值、水的第三横向弛豫时间和脂肪的第三横向弛豫时间不变，依据第二水脂组织温度图像、水信号第三强度幅值、水信号第三相位值、水信号第三强度幅值、水信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘对预设定的磁共振信号模型进行第三次拟合，获得使得第三次拟合后的信号强度与拟合前的信号强度差值最小的水信号第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像。
具体地，第四计算单元305配置成依据算式
Figure PCTCN2017119483-appb-000020
第三次拟合预设定的磁共振信号模型。
可以理解地，第四计算单元305可以执行步骤S205。
综上所述，该磁共振温度成像方法与装置通过两步迭代温度估计的算法提高了当前时刻的水脂组织温度图像的准确度和精确度，磁共振信号模型包含有脂肪多峰，同时估计得到了信号强度与拟合前的信号强度差值最小的水信号第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像，保证了温度结果的无偏性。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，也可以通过其它的方式实现。以上所描述的装置实施例仅仅是示意性的，例如，附图中的流程图和框图显示了根据本发明的多个实施例的装置、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段或代码的一部分，所述模块、程序段或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现方式中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个连续的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或动作的专用的基于硬件的***来实现，或者可以用专用硬件与计算机指令的组合来实现。
另外，在本发明各个实施例中的各功能模块可以集成在一起形成一个独立的部分，也可以是各个模块单独存在，也可以两个或两个以上模块集成形成一个独立的部分。
所述功能如果以软件功能模块的形式实现并作为独立的产品销售或使用时，可以存储 在一个计算机可读取存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
以上所述仅为本发明的优选实施例而已，并不用于限制本发明，对于本领域的技术人员来说，本发明可以有各种更改和变化。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。应注意到：相似的标号和字母在下面的附图中表示类似项，因此，一旦某一项在一个附图中被定义，则在随后的附图中不需要对其进行进一步定义和解释。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应所述以权利要求的保护范围为准。
需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。

Claims (10)

  1. 一种磁共振温度成像方法，其特征在于，所述磁共振温度成像方法包括：
    依据预设定的磁共振信号模型、预先赋予的初始水脂组织温度图像以及水脂分离算法，获得水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘；
    依据初始水脂组织温度图像、水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘第一次拟合预设定的磁共振信号模型，获得使得第一次拟合后的信号强度与拟合前的信号强度差值最小的水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间、主磁场不均匀造成的第二场飘和第二水脂组织温度图像；
    保持第二水脂组织温度图像不变，依据第二水脂组织温度图像、水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间和主磁场不均匀造成的第二场飘第二次拟合预设定的磁共振信号模型，获得使得第二次拟合后的信号强度与拟合前的信号强度差值最小的水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘；
    保持水信号第三相位值、脂肪信号第三相位值、水的第三横向弛豫时间和脂肪的第三横向弛豫时间不变，依据第二水脂组织温度图像、水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘第三次拟合预设定的磁共振信号模型，获得使得第三次拟合后的信号强度与拟合前的信号强度差值最小的水信号第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像。
  2. 根据权利要求1所述的磁共振温度成像方法，其特征在于，在所述保持第二水脂组织温度图像不变，依据第二水脂组织温度图像、水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间和主磁场不均匀造成的第二场飘第二次拟合预设定的磁共振信号模型，获得使得第二次拟合后的信号强度与拟合前的信号强度差值最小的水信号 第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘的步骤之前，所述磁共振温度成像方法包括：
    对第二水脂组织温度图像采用低通滤波器进行平滑处理从而获得平滑处理后的第二水脂组织温度图像。
  3. 根据权利要求2所述的磁共振温度成像方法，其特征在于，依据算式
    Figure PCTCN2017119483-appb-100001
    第二水脂组织温度图像采用低通滤波器进行平滑处理从而获得平滑处理后的第二水脂组织温度图像，其中，ΔT i为第i个像素的当前温度估计值，
    Figure PCTCN2017119483-appb-100002
    为所有像素点温度值的均值，
    Figure PCTCN2017119483-appb-100003
    为第i个像素点平滑处理后的温度值。
  4. 根据权利要求1所述的磁共振温度成像方法，其特征在于，所述预设定的磁共振信号模型为
    Figure PCTCN2017119483-appb-100004
    其中，S n为在回波时间TE n下的信号强度；W为水信号强度值，F为脂肪信号强度值，γ为旋磁比，B 0为主磁场强度，α为水中氢质子温度系数，P为脂肪峰的个数，对应的相对幅值和化学位移分别为β p和f F,p，且
    Figure PCTCN2017119483-appb-100005
    为水的横向弛豫时间， 为脂肪的横向弛豫时间，f b为由于主磁场不均匀造成的场飘，N是总共采集回波个数；ΔT为水脂组织温度图像。
  5. 根据权利要求4所述的磁共振温度成像方法，其特征在于，依据算式
    Figure PCTCN2017119483-appb-100007
    第一次拟合预设定的磁共振信号模型。
  6. 一种磁共振温度成像装置，其特征在于，所述磁共振温度成像装置包括：
    第一计算单元，配置成依据预设定的磁共振信号模型、预先赋予的初始水脂组织温度图像以及水脂分离算法，获得水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘；
    第二计算单元，配置成依据初始水脂组织温度图像、水信号第一强度幅值、水信号第一相位值、脂肪信号第一强度幅值、脂肪信号第一相位值、水的第一横向弛豫时间、脂肪的第一横向弛豫时间和主磁场不均匀造成的第一场飘第一次拟合预设定的磁共振信号模型，获得使得第一次拟合后的信号强度与拟合前的信号强度差值最小的水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间、主磁场不均匀造成的第二场飘和第二水脂组织温度图像；
    第三计算单元，配置成保持第二水脂组织温度图像不变，依据第二水脂组织温度图像、水信号第二强度幅值、水信号第二相位值、脂肪信号第二强度幅值、脂肪信号第二相位值、水的第二横向弛豫时间、脂肪的第二横向弛豫时间和主磁场不均匀造成的第二场飘第二次拟合预设定的磁共振信号模型，获得使得第二次拟合后的信号强度与拟合前的信号强度差值最小的水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘；
    第四计算单元，配置成保持水信号第三相位值、脂肪信号第三相位值、水的第三横向弛豫时间和脂肪的第三横向弛豫时间不变，依据第二水脂组织温度图像、水信号第三强度幅值、水信号第三相位值、脂肪信号第三强度幅值、脂肪信号第三相位值、水的第三横向弛豫时间、脂肪的第三横向弛豫时间和主磁场不均匀造成的第三场飘对预设定的磁共振信号模型进行第三次拟合，获得使得第三次拟合后的信号强度与拟合前的信号强度差值最小的水信号第四强度幅值、脂肪信号第四强度幅值、主磁场不均匀造成的第四场飘以及当前时刻的水脂组织温度图像。
  7. 根据权利要求6所述的磁共振温度成像装置，其特征在于，所述磁共振温度成像装置还包括：
    滤波单元，配置成对第二水脂组织温度图像采用低通滤波器进行平滑处理从而获得平滑处理后的第二水脂组织温度图像。
  8. 根据权利要求7所述的磁共振温度成像装置，其特征在于，所述滤波单元配置成依据算式
    Figure PCTCN2017119483-appb-100008
    第二水脂组织温度图像采用低通滤波器进行平滑 处理从而获得平滑处理后的第二水脂组织温度图像，其中，ΔT i为第i个像素的当前温度估计值，
    Figure PCTCN2017119483-appb-100009
    为所有像素点温度值的均值，
    Figure PCTCN2017119483-appb-100010
    为第i个像素点平滑处理后的温度值。
  9. 根据权利要求6所述的磁共振温度成像装置，其特征在于，所述预设定的磁共振信号模型为
    Figure PCTCN2017119483-appb-100011
    ，其中，S n为在回波时间TE n下的信号强度；W为水信号强度值，F为脂肪信号强度值，γ为旋磁比，B 0为主磁场强度，α为水中氢质子温度系数，P为脂肪峰的个数，对应的相对幅值和化学位移分别为β p和f F,p，且
    Figure PCTCN2017119483-appb-100012
    为水的横向弛豫时间，
    Figure PCTCN2017119483-appb-100013
    为脂肪的横向弛豫时间，f b为由于主磁场不均匀造成的场飘，N是总共采集回波个数；ΔT为水脂组织温度图像。
  10. 根据权利要求9所述的磁共振温度成像装置，其特征在于，所述第二计算单元配置成依据算式
    Figure PCTCN2017119483-appb-100014
    第一次拟合预设定的磁共振信号模型。
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