CN104274176B - The non-invasive measurement method of brain tissue microstructure - Google Patents
The non-invasive measurement method of brain tissue microstructure Download PDFInfo
- Publication number
- CN104274176B CN104274176B CN201310289620.7A CN201310289620A CN104274176B CN 104274176 B CN104274176 B CN 104274176B CN 201310289620 A CN201310289620 A CN 201310289620A CN 104274176 B CN104274176 B CN 104274176B
- Authority
- CN
- China
- Prior art keywords
- cell
- image
- diffusion
- volume ratio
- pixel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- 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
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- High Energy & Nuclear Physics (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Radiology & Medical Imaging (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
Abstract
The non-invasive measurement method of brain tissue microstructure, including use MR diffusion-weighted imaging brain tissue；Determine the actual image signal intensity of each pixel in the magnetic resonance image（Si）；Establish the calculating image intensity signal of each pixel in the magnetic resonance image（Sbi）With the weights of the MR diffusion-weighted imaging（bi）Between functional relation；With the extracellular space volume ratio by each pixel in the magnetic resonance image（fECS）, the cell volume ratio（fcell）, the cerebral blood vessel volume ratio（fvas）, the extracellular space diffusion coefficient（DECS）, the cellular invasion coefficient（Dcell）With the cerebral blood vessel diffusion coefficient（Dvas）Reconstruct the magnetic resonance image.
Description
Technical field
The present invention relates to a kind of measurement methods of microstructure, more particularly to one kind measuring brain tissue by magnetic resonance imaging
The non-invasive measurement method of microstructure.
Background technology
Magnetic resonance（magnetic resonance imaging, MRI）Since it is differentiated without ionization damage, high soft tissue
The characteristics of rate, is widely used to the imaging of central nervous system in addition to the sensibility of chemical composition.With magnetic resonance moisture
The application of the new technologies such as sub- diffusion-sensitive imaging technique is gradually ripe, MR diffusion-weighted imaging occurs（diffusion-
weighted imaging, DWI）, and may be implemented to solve the diffusion coefficient of hydrone in pixel, it and guides
The diagnosis and differential diagnosis of clinical disease.
When MR diffusion-weighted imaging, between high-frequency impulse and data acquisition, in addition a pair of bipolar diffusion-sensitive ladder
Spend pulse.First diffusion-sensitive gradient pulses makes proton spin go phase, if the not movement of hydrone, second expansion
Scattered sensitive gradient pulses can make its complete complex phase position.In tissue the diffusion degree of freedom of hydrone can influence Magnetic Resonance Diffusion Weighting at
As the decaying of image intensity signal, water diffusion is freer on the application direction of diffusion sensitising gradient field, picture signal decaying
It is more apparent.In magnetic resonance diffusion imaging, if hydrone random motion is limited, picture signal is high RST.Picture signal is strong
Spend S=S0 e-b*D（Wherein, S0When not apply diffusion-sensitive gradient pulses, the signal strength of pixel in nuclear-magnetism image；S is
Apply the signal strength of pixel in nuclear-magnetism image after diffusion-sensitive gradient pulses；The weights of b MR diffusion-weighted imagings, it is single
Position mm2/ s can change the numerical value of b by changing diffusion-sensitive gradient pulses；D is diffusion-weighted on water diffusion direction
Coefficient, unit s/mm2）.
Currently, the expansion to each pixel hydrone in nuclear-magnetism image has may be implemented in MR diffusion-weighted imaging
Scattered coefficient is solved, and the diagnosis and differential diagnosis of clinical disease is and guided.But this coefficient, which is intraor extracellular hydrone, to be expanded
It loads dynamic concentrated expression in bulk, is referred to as apparent diffusion coefficient（apparent diffusion coefficient, ADC）, can not
Distinguish intraor extracellular diffusion motion.And the pathogenetic different phase of brain, the volumetric ratio of intraor extracellular and the diffusion coefficient of hydrone
Also dramatically different.For example, cerebral ischemia early stage, nerve cell swelling, brain extracellular space（extracellular space,
ECS）Shrinkage, water diffusion are limited；Cerebral ischemia late period, neuronal cell death, brain extracellular space volume are significantly expanded, moisture
Sub- diffusion coefficient increases.
Invention content
The object of the present invention is to provide a kind of non-invasive measurement methods of brain tissue microstructure, to obtain in brain tissue cell
The difference of free surface moisture diffusion.
The present invention provides a kind of non-invasive measurement methods of brain tissue microstructure, including use Magnetic Resonance Diffusion Weighting at
As brain tissue, each weights b for corresponding to the MR diffusion-weighted imaging is obtainediBrain tissue a plurality of magnetic resonance image,
Wherein i is integer and i=1.2.3.4.5.6 ...；Determine the actual image signal intensity of each pixel in the magnetic resonance image
Si；It defines one and calculates image intensity signal S（bi）, establish the calculating image of each pixel in the magnetic resonance image
Signal strength S（bi）With the weights b of the MR diffusion-weighted imagingiBetween functional relation, the wherein functional relation
For：
,
Wherein：S0When not apply diffusion-sensitive gradient pulses, the theoretical letter of each pixel in the magnetic resonance image
Number intensity, fECSFor the extracellular space volume ratio of brain tissue, fcellFor the cell volume ratio of brain tissue, fvasFor brain tissue
Cerebral blood vessel volume ratio, DECSFor the extracellular space diffusion coefficient of brain tissue, DcellFor the cellular invasion system of brain tissue
Number, DvasFor the cerebral blood vessel diffusion coefficient of brain tissue；By the actual image signal intensity SiWith described image signal strength S
（bi）Variance calculated by least square method on the basis of brain tissue measured zone water diffusion amount of movement grade
To the extracellular space volume ratio f of each pixel in the magnetic resonance imageECS, the cell volume ratio fcell、
The cerebral blood vessel volume ratio fvas, the extracellular space diffusion coefficient DECS, the cellular invasion coefficient DcellWith it is described
Cerebral blood vessel diffusion coefficient Dvas；With the extracellular space volume ratio by each pixel in the magnetic resonance image
fECS, the cell volume ratio fcell, the cerebral blood vessel volume ratio fvas, the extracellular space diffusion coefficient DECS, institute
State cellular invasion coefficient DcellWith the cerebral blood vessel diffusion coefficient DvasReconstruct the magnetic resonance image.
In another schematical embodiment of the non-invasive measurement method of brain tissue microstructure, it is total to solve the magnetic
Shake the extracellular space volume ratio f of each pixel in imageECS, the cell volume ratio fcell, the brain
Interior capacity of blood vessel ratio fvas, the extracellular space diffusion coefficient DECS, the cellular invasion coefficient DcellWith the intracerebral blood
Pipe diffusion coefficient DvasEquation group be：
,
,
,
,
, and
,
SiBe weights be biUnder the premise of, by the imaging for the brain tissue that the MR diffusion-weighted imaging obtains
The actual signal intensity value of each pixel in region, i are integer and i=1.2.3.4.5.6 ....
Description of the drawings
The following drawings only does schematic illustration and explanation to the present invention, not delimit the scope of the invention.
When Fig. 1 to Fig. 3 is used to show that diffusion-sensitive gradient pulses are applied to the different directions of nuclear-magnetism image, by nuclear-magnetism image
In each pixel extracellular space volume ratio（fECS）The image drawn.
When fig. 4 to fig. 6 is used to show that diffusion-sensitive gradient pulses are applied to the different directions of nuclear-magnetism image, by nuclear-magnetism image
In each pixel cell volume ratio（fcell）The image drawn.
When Fig. 7 to Fig. 9 is used to show that diffusion-sensitive gradient pulses are applied to the different directions of nuclear-magnetism image, by nuclear-magnetism image
In each pixel cerebral blood vessel volume ratio（fvas）The image drawn.
When Figure 10 to Figure 12 is used to show that diffusion-sensitive gradient pulses are applied to the different directions of nuclear-magnetism image, by nuclear-magnetism figure
The extracellular space diffusion coefficient of each pixel as in（DECS）The image drawn.
When Figure 13 to Figure 15 is used to show that diffusion-sensitive gradient pulses are applied to the different directions of nuclear-magnetism image, by nuclear-magnetism figure
The cellular invasion coefficient of each pixel as in（Dcell）The image drawn.
When Figure 16 to Figure 18 is used to show that diffusion-sensitive gradient pulses are applied to the different directions of nuclear-magnetism image, by nuclear-magnetism figure
The cerebral blood vessel diffusion coefficient of each pixel as in（Dvas）The image drawn.
Specific implementation mode
In order to which the technical features, objects and effects to invention are more clearly understood, now illustrate the specific reality of the present invention
Apply mode.
The non-invasive measurement method of brain tissue microstructure, using diffusion-weighted MR imaging, for brain tissue
The nuclear-magnetism detection of interest region is measured, obtains the nuclear-magnetism image of brain tissue, and can obtain in nuclear-magnetism image, each pixel
Actual image signal intensity S.During using MR diffusion-weighted imaging, diffusion sensitising gradient can be changed by changing
Pulse adjusts the weights of MR diffusion-weighted imaging, to obtain the weights corresponding to different MR diffusion-weighted imagings
biNuclear-magnetism image.
It defines one and calculates image intensity signal S（bi）, establish the calculating picture signal of each pixel in nuclear-magnetism image
Intensity S（bi）With the weights b of MR diffusion-weighted imagingiBetween functional relation, and the calculating figure being theoretically calculated
As signal strength S（bi）With actual image signal intensity SiEqual, difference lies in actual image signal intensity SiFor measured value,
And calculate image intensity signal S（bi）It is to be calculated by mathematical model.In the non-invasive measurement method of brain tissue microstructure,
Brain tissue is regarded as to three compartment models being made of nerve cell, extracellular space ECS and cerebral blood vessel.Hydrone is in each room
The contribution totally spread in indoor diffusion couple magnetic resonance pixel is related to the volume ratio that each chamber is shared in brain tissue, i.e.,
It is f by the apparent diffusion coefficient ADC that nuclear-magnetism image is reflectedECS*DECS+fcell*Dcell+fvas*DvasThe sum of.Wherein, fECS、
fcell、fvasThe respectively extracellular space volume ratio, the cell volume ratio of brain tissue and the intracerebral of brain tissue of brain tissue
Capacity of blood vessel ratio；DECS、Dcell、DvasThe respectively cellular invasion system of the extracellular space diffusion coefficient of brain tissue, brain tissue
The cerebral blood vessel diffusion coefficient of number and brain tissue.By image intensity signal expression formula S=S of nuclear-magnetism image0 e-b*D, in conjunction with upper
Three compartment models are stated, the calculating image intensity signal S of each pixel in nuclear-magnetism image is obtained（bi）With Magnetic Resonance Diffusion Weighting
The weights b of imagingiBetween functional relation be：
,
Wherein, S0When not apply diffusion-sensitive gradient pulses, brain tissue nuclear-magnetism image in the imaging region of brain tissue
The signal strength of each pixel.
On the basis of brain tissue measured zone water diffusion amount of movement grade, obtained using least square method numerical solution
To the extracellular space volume ratio f of each pixel in nuclear-magnetism imageECS, cell volume ratio fcell, cerebral blood vessel hold
Product ratio fvas, extracellular space diffusion coefficient DECS, cellular invasion coefficient DcellWith cerebral blood vessel diffusion coefficient Dvas.In brain group
In a kind of exemplary embodiment of non-invasive measurement method for knitting microstructure, actual image signal intensity SiWith calculating picture signal
Intensity S（bi）Variance be：, and in order to solve extracellular space volume ratio fECS、Cell volume ratio
Rate fcell, cerebral blood vessel volume ratio fvas、Extracellular space diffusion coefficient DECS, cellular invasion coefficient DcellExpand with cerebral blood vessel
Dissipate coefficient DvasThis six parameters at least need to obtain six equations about these parameters, can be total by six different magnetic
Shake the weights b of Diffusion-Weighted MR ImagingiTo obtain different actual image signal intensity SiWith calculating image intensity signal S（bi）,
Middle footmark i represents the weights b of i-th of MR diffusion-weighted imagingi.By least square method, obtain about extracellular space
Volume ratio fECS, cell volume ratio fcell, cerebral blood vessel volume ratio fvas, extracellular space diffusion coefficient DECS, cell expand
Dissipate coefficient DcellWith cerebral blood vessel diffusion coefficient DvasEquation group be：
,
,
,
,
,
。
Thus solving equations obtain the extracellular space volume ratio f of each pixel of nuclear-magnetism imageECS, cell hold
Product ratio fcell, cerebral blood vessel volume ratio fvas, extracellular space diffusion coefficient DECS, cellular invasion coefficient DcellWith intracerebral blood
Pipe diffusion coefficient Dvas.Least square method is improved it is of course possible to use the weights more than six MR diffusion-weighted imagings
Solving precision.
By the extracellular space volume ratio f of each pixel of nuclear-magnetism imageECS, cell volume ratio fcell, intracerebral
Capacity of blood vessel ratio fvas, extracellular space diffusion coefficient DECS, cellular invasion coefficient DcellWith cerebral blood vessel diffusion coefficient DvasIt is right
Nuclear-magnetism image reconstruction.
Fig. 1 to Figure 18 comes from the same nuclear-magnetism image, and each view is reconstructed the nuclear-magnetism image respectively.Such as Fig. 1,2 and 3
It is shown, when wherein Fig. 1 is that diffusion-sensitive gradient pulses are applied to the X-direction of nuclear-magnetism image, by each pixel in nuclear-magnetism image
The extracellular space volume ratio f of pointECSThe image drawn, each pixel gray level or color change represent difference in image
Extracellular space volume ratio size；When Fig. 2 is that diffusion-sensitive gradient pulses are applied to the Y direction of nuclear-magnetism image, by core
The extracellular space volume ratio f of each pixel in magnetic imageECSThe image drawn, in image each pixel gray level or
Color change represents different extracellular space volume ratio sizes；Fig. 3 is that diffusion-sensitive gradient pulses are applied to nuclear-magnetism image
Z-direction when, by the extracellular space volume ratio f of each pixel in nuclear-magnetism imageECSThe image drawn, in image
Each pixel gray level or color change represent different extracellular space volume ratio sizes.
As shown in Fig. 4,5 and 6, when wherein Fig. 4 is that diffusion-sensitive gradient pulses are applied to the X-direction of nuclear-magnetism image, by
The cell volume ratio f of each pixel in nuclear-magnetism imagecellThe image drawn, each pixel gray level or color in image
Variation represents different extracellular space volume ratio sizes；Fig. 5 is the Y-axis that diffusion-sensitive gradient pulses are applied to nuclear-magnetism image
When direction, by the cell volume ratio f of each pixel in nuclear-magnetism imagecellThe image drawn, each pixel in image
Gray scale or color change represent different extracellular space volume ratio sizes；Fig. 6 is that diffusion-sensitive gradient pulses are applied to core
When the Z-direction of magnetic image, by the cell volume ratio f of each pixel in nuclear-magnetism imagecellThe image drawn, in image
Each pixel gray level or color change represent different cell volume ratio magnitudes.
As shown in Fig. 7,8 and 9, when wherein Fig. 7 is that diffusion-sensitive gradient pulses are applied to the X-direction of nuclear-magnetism image, by
The cerebral blood vessel volume ratio f of each pixel in nuclear-magnetism imagevasThe image drawn, in image each pixel gray level or
Color change represents different extracellular space volume ratio sizes；Fig. 8 is that diffusion-sensitive gradient pulses are applied to nuclear-magnetism image
Y direction when, by the cerebral blood vessel volume ratio f of each pixel in nuclear-magnetism imagevasThe image drawn, it is each in image
A pixel gray level or color change represent different extracellular space volume ratio sizes；Fig. 9 is diffusion-sensitive gradient pulses
When being applied to the Z-direction of nuclear-magnetism image, by the cerebral blood vessel volume ratio f of each pixel in nuclear-magnetism imagevasIt is drawn
Image, each pixel gray level or color change represent different cell volume ratio magnitudes in image.
As shown in Figure 10,11 and 12, wherein Figure 10 is the X-direction that diffusion-sensitive gradient pulses are applied to nuclear-magnetism image
When, by the extracellular space diffusion coefficient D of each pixel in nuclear-magnetism imageECSThe image drawn, each pixel in image
Gray scale or color change represent different extracellular space diffusion coefficient DsECSSize；Figure 11 applies for diffusion-sensitive gradient pulses
In the Y direction of nuclear-magnetism image, by the extracellular space diffusion coefficient D of each pixel in nuclear-magnetism imageECSThe figure drawn
Picture, each pixel gray level or color change represent different extracellular space diffusion coefficient Ds in imageECSSize；Figure 12 is to expand
When scattered sensitive gradient pulses are applied to the Z-direction of nuclear-magnetism image, expanded by the extracellular space of each pixel in nuclear-magnetism image
Dissipate coefficient DECSThe image drawn, each pixel gray level or color change represent different extracellular space diffusions in image
Coefficient DECSSize.
As shown in Figure 13,14 and 15, wherein Figure 13 is the X-direction that diffusion-sensitive gradient pulses are applied to nuclear-magnetism image
When, by the cellular invasion coefficient D of each pixel in nuclear-magnetism imagecellThe image drawn, each pixel gray level in image
Or color change represents different cellular invasion coefficient DcellSize；Figure 14 is that diffusion-sensitive gradient pulses are applied to nuclear-magnetism image
Y direction when, by the cellular invasion coefficient D of each pixel in nuclear-magnetism imagecellThe image drawn, each picture in image
Vegetarian refreshments gray scale or color change represent different cellular invasion coefficient DcellSize；Figure 15 is applied to for diffusion-sensitive gradient pulses
When the Z-direction of nuclear-magnetism image, by the cellular invasion coefficient D of each pixel in nuclear-magnetism imagecellThe image drawn, image
In each pixel gray level or color change represent different cellular invasion coefficient DcellSize.
As shown in Figure 16,17 and 18, wherein Figure 16 is the X-direction that diffusion-sensitive gradient pulses are applied to nuclear-magnetism image
When, by the cerebral blood vessel diffusion coefficient D of each pixel in nuclear-magnetism imagevasThe image drawn, each pixel ash in image
Degree or color change represent different cerebral blood vessel diffusion coefficient DsvasSize；Figure 17 is that diffusion-sensitive gradient pulses are applied to core
When the Y direction of magnetic image, by the cerebral blood vessel diffusion coefficient D of each pixel in nuclear-magnetism imagevasThe image drawn, figure
Each pixel gray level or color change represent different cerebral blood vessel diffusion coefficient Ds as invasSize；Figure 18 is diffusion-sensitive
When gradient pulse is applied to the Z-direction of nuclear-magnetism image, by the cerebral blood vessel diffusion coefficient D of each pixel in nuclear-magnetism imagevas
The image drawn, each pixel gray level or color change represent different cerebral blood vessel diffusion coefficient Ds in imagevasSize.
Herein, " schematic " expression " serving as example, example or explanation " should not will be described herein as " showing
Any diagram, the embodiment of meaning property " are construed to a kind of preferred or more advantageous technical solution.
It should be appreciated that although this specification describes according to various embodiments, not each embodiment only includes one
A independent technical solution, this description of the specification is merely for the sake of clarity, and those skilled in the art should will say
As a whole, the technical solutions in the various embodiments may also be suitably combined for bright book, and forming those skilled in the art can be with
The other embodiment of understanding.
The series of detailed descriptions listed above is illustrated only for possible embodiments of the invention,
They are all without departing from equivalent embodiment made by technical spirit of the present invention or change not to limit the scope of the invention
It should all be included in the protection scope of the present invention.
Claims (2)
1. the non-invasive measurement method of brain tissue microstructure, including：
Using MR diffusion-weighted imaging brain tissue, each weights b for corresponding to the MR diffusion-weighted imaging is obtainediBrain
A plurality of magnetic resonance image of tissue, wherein i are integer i=1,2,3,4,5,6 ..., and i >=6；
Measure the actual image signal intensity S of each pixel in the magnetic resonance imagei；
It defines one and calculates image intensity signal S（bi）, establish the calculating image of each pixel in the magnetic resonance image
Signal strength S（bi）With the weights b of the MR diffusion-weighted imagingiBetween functional relation, the wherein functional relation
For：
,
Wherein：S0When not apply diffusion-sensitive gradient pulses, the theory signal of each pixel is strong in the magnetic resonance image
Degree,
fECSFor the extracellular space volume ratio of brain tissue,
fcellFor the cell volume ratio of brain tissue,
fvasFor the cerebral blood vessel volume ratio of brain tissue,
DECSFor the extracellular space diffusion coefficient of brain tissue,
DcellFor the cellular invasion coefficient of brain tissue,
DvasFor the cerebral blood vessel diffusion coefficient of brain tissue；
By the actual image signal intensity SiWith the calculating image intensity signal S（bi）Variance, pass through least square method meter
Calculation obtains the extracellular space volume ratio f of each pixel in the magnetic resonance imageECS, the cell volume ratio
fcell, the cerebral blood vessel volume ratio fvas, the extracellular space diffusion coefficient DECS, the cellular invasion coefficient DcellWith
The cerebral blood vessel diffusion coefficient Dvas；With
By the extracellular space volume ratio f of each pixel in the magnetic resonance imageECS, the cell volume ratio
fcell, the cerebral blood vessel volume ratio fvas, the extracellular space diffusion coefficient DECS, the cellular invasion coefficient DcellWith
The cerebral blood vessel diffusion coefficient DvasReconstruct the magnetic resonance image.
2. the non-invasive measurement method of brain tissue microstructure as described in claim 1, wherein solving in the magnetic resonance image
The extracellular space volume ratio f of each pixelECS, the cell volume ratio fcell, the cerebral blood vessel holds
Product ratio fvas, the extracellular space diffusion coefficient DECS, the cellular invasion coefficient DcellIt is spread with the cerebral blood vessel and is
Number DvasEquation group be：
,
,
,
,
, and
。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310289620.7A CN104274176B (en) | 2013-07-11 | 2013-07-11 | The non-invasive measurement method of brain tissue microstructure |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310289620.7A CN104274176B (en) | 2013-07-11 | 2013-07-11 | The non-invasive measurement method of brain tissue microstructure |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104274176A CN104274176A (en) | 2015-01-14 |
| CN104274176B true CN104274176B (en) | 2018-10-30 |
Family
ID=52249883
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310289620.7A Active CN104274176B (en) | 2013-07-11 | 2013-07-11 | The non-invasive measurement method of brain tissue microstructure |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104274176B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105078456A (en) * | 2015-02-15 | 2015-11-25 | 北京大学第三医院 | Noninvasive measuring method of microstructure of biological tissue |
| JP6763719B2 (en) * | 2015-12-07 | 2020-09-30 | パナソニック株式会社 | Biometric information measuring device, biometric information measuring method and program |
| EP3688480B1 (en) * | 2017-09-26 | 2024-05-29 | Koninklijke Philips N.V. | Non-invasive estimation of prostate tissue composition based on multi-parametric mri data |
| CN114646913B (en) * | 2020-12-21 | 2023-06-02 | 北京大学第三医院（北京大学第三临床医学院） | Non-invasive measurement method for microstructure of biological tissue |
| CN118013791A (en) * | 2024-02-04 | 2024-05-10 | 北京大学第三医院（北京大学第三临床医学院） | Method and system for acquiring extracellular space internal molecular motion parameters |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5488297A (en) * | 1994-07-19 | 1996-01-30 | The Regents Of The University Of California | Three dimensional anisotropy contrast magnetic resonance imaging |
| CN1725029A (en) * | 2004-07-20 | 2006-01-25 | 北京大学第三医院 | The apparatus and method that are used for correcting deforming of diffusion image |
| CN102238908A (en) * | 2009-12-07 | 2011-11-09 | 北京大学第三医院 | Method for measuring physiological parameters in cerebral interstitial fluid and cerebral extracellular space |
| CN102525529A (en) * | 2010-10-28 | 2012-07-04 | 株式会社东芝 | Medical image noise reduction based on weighted anisotropic diffusion |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7634302B2 (en) * | 2004-07-09 | 2009-12-15 | General Electric Company | Method for differentiating tissues in magnetic resonance imaging |
| US9002428B2 (en) * | 2011-01-28 | 2015-04-07 | The Board Of Trustees Of The Leland Stanford Junior University | Methods for detecting abnormalities and degenerative processes in soft tissue using magnetic resonance imaging (MRI) |
-
2013
- 2013-07-11 CN CN201310289620.7A patent/CN104274176B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5488297A (en) * | 1994-07-19 | 1996-01-30 | The Regents Of The University Of California | Three dimensional anisotropy contrast magnetic resonance imaging |
| CN1725029A (en) * | 2004-07-20 | 2006-01-25 | 北京大学第三医院 | The apparatus and method that are used for correcting deforming of diffusion image |
| CN102238908A (en) * | 2009-12-07 | 2011-11-09 | 北京大学第三医院 | Method for measuring physiological parameters in cerebral interstitial fluid and cerebral extracellular space |
| CN102525529A (en) * | 2010-10-28 | 2012-07-04 | 株式会社东芝 | Medical image noise reduction based on weighted anisotropic diffusion |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104274176A (en) | 2015-01-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104274176B (en) | The non-invasive measurement method of brain tissue microstructure | |
| Fan et al. | Validation of diffusion MRI estimates of compartment size and volume fraction in a biomimetic brain phantom using a human MRI scanner with 300 mT/m maximum gradient strength | |
| Koopmans et al. | Multi-echo fMRI of the cortical laminae in humans at 7 T | |
| Komlosh et al. | Pore diameter mapping using double pulsed-field gradient MRI and its validation using a novel glass capillary array phantom | |
| Niesporek et al. | Partial volume correction for in vivo 23Na-MRI data of the human brain | |
| Chen et al. | Quantitative ultra-fast MRI of HPMC swelling and dissolution | |
| US20140296700A1 (en) | Magnetic Resonance Imaging (MRI) Based Quantitative Liver Perfusion Analysis | |
| Viallon et al. | Head‐to‐head comparison of eight late gadolinium‐enhanced cardiac MR (LGE CMR) sequences at 1.5 tesla: from bench to bedside | |
| Chen et al. | Effects of rejecting diffusion directions on tensor-derived parameters | |
| Benjamini et al. | Imaging local diffusive dynamics using diffusion exchange spectroscopy MRI | |
| CN106793971A (en) | MR imaging apparatus | |
| ES2895451T3 (en) | MRI Method for Quantifying the Amount of Iron in Tissues Using Diffusion Magnetic Resonance Imaging | |
| Cai et al. | Rapid detection of the presence of diffusion exchange | |
| JP2018075075A5 (en) | ||
| Oshio et al. | Interpretation of diffusion MR imaging data using a gamma distribution model | |
| Yu et al. | Can anomalous diffusion models in magnetic resonance imaging be used to characterise white matter tissue microstructure? | |
| Miller et al. | Estimation of transversely isotropic material properties from magnetic resonance elastography using the optimised virtual fields method | |
| BR112014027060B1 (en) | Method for magnetic resonance (MR) and/or MR imaging | |
| Lorenz et al. | Anisotropic phantoms for quantitative diffusion tensor imaging and fiber-tracking validation | |
| Puri et al. | An enhanced multi-fiber reconstruction technique using adaptive gradient directions coupled with moncw model in diffusion MRI | |
| Sadighi et al. | Low-frequency conductivity tensor imaging with a single current injection using DT-MREIT | |
| Sairanen et al. | A novel measure of reliability in Diffusion Tensor Imaging after data rejections due to subject motion | |
| Sapkota et al. | Characterization of spinal cord white matter by suppressing signal from hindered space. A Monte Carlo simulation and an ex vivo ultrahigh-b diffusion-weighted imaging study | |
| Cho et al. | Visualization of inhomogeneous local magnetic field gradient due to susceptibility contrast | |
| Li et al. | A simple B1 correction method for dynamic contrast-enhanced MRI |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |