CN105796094A - Ventricular premature beat abnormal activation site positioning method based on ECGI (electrocardiographic imaging) - Google Patents
Ventricular premature beat abnormal activation site positioning method based on ECGI (electrocardiographic imaging) Download PDFInfo
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Abstract
The invention discloses a ventricular premature beat abnormal activation site positioning method based on ECGI (electrocardiographic imaging). According to the method, by establishing a combined collection framework of 64 lead body surface potential data and computed tomography imaging, a personalized heart-trunk model is obtained; by Tikhonov regularization, the ECG (Electrocardiograph) inverse problem is solved; an epicardial potential is reconstructed so as to accurately position a ventricular premature beat abnormal activation site. The ventricular premature beat abnormal activation site positioning method has important actual application value.
Description
Technical field
The invention belongs to cardiac electrophysiology analysis technical field, be specifically related to a kind of ventricular premature contraction based on ECGI
Abnormal exciting independent positioning method.
Background technology
Electrocardiography (Electrocardiography) passes through depolarization in body surface record heart beat cycles
The potential change caused with process of repolarization, discloses one of cardiac electrophysiology activity very with becoming non-intrusion type
Important method.If regarding heart as electric field source, then be just dispersed with phase in heart to the space of body surface
The electric field answered, can record the current potential of each position at body surface.The electro physiology inverting of so-called heart, it is simply that logical
Cross body surface potential distribution, infer the exception that the electrical activity in heart causes due to myocardial ischemia from outside to inside
Situation.The disease that doctor is correlated with by electrocardiographic diagnosis heart clinically, this process can also regard the heart as
Dirty electro physiology inverting, what only doctor relied on is qualitative judgement based on experience accumulation, has the strongest
Subjectivity.
Along with development of modern scientific technology, become with the electro physiology inverting of Computer Simulation based on digital heart model
For possible.Rudy et al. proposes the concept of electrocardiograph function imaging (ECGI), and utilizes 256 electrode notes
Record body surface potential, obtains trunk and the geometry information of heart by plain CT simultaneously, and then sets up border
Meta-model derives association body surface potential and the transition matrix of epicardial potential, finally utilizes Tikhonov canonical
Change method and broad sense least residual algorithm current potential, electrocardiogram, isochrone and depolarizing type to heart surface
Etc. rebuilding.But ECGI is not the most widely applied to clinically, which reflects ECGI itself
Including it, the some defects existed, require that up to 256 electrodes of use record the body surface potential of patient, this
Not only increase the cost of inspection, add the complexity etc. of operation simultaneously.
Diagnosis Main Basis 12 lead electrocardiogram to ventricular premature contraction the most clinically, but such method is only
Ventricular premature contraction can be carried out tentative diagnosis, it is impossible to provide the pre-set time that the position of premature beat, premature beat such as occur
Etc. more detailed information.On the other hand, in the ablative surgery of ventricular premature contraction, surgeon also by means of
The means of intrusive mood directly measure the bioelectrical activity of cardiac objects position, the exciting point of exception to ventricular premature contraction
Position.But the method for intrusive mood is inefficient, and there is certain risk.Therefore, how from existing
Some diagnosis and treatment means are set out, and exciting point abnormal to ventricular premature contraction positions in vitro, and becoming one extremely has
Studying a question of meaning.
Summary of the invention
The invention provides the abnormal exciting independent positioning method of a kind of ventricular premature contraction based on ECGI, the method is passed through
Record body surface potential distribution and Computed tomography, set up personalized heart-human trunk model, then
By electro physiology inverting, the position of premature beat point is accurately positioned.
The abnormal exciting independent positioning method of a kind of ventricular premature contraction based on ECGI, comprises the steps:
(1) gather the 64 of ventricular premature contraction patient to lead body surface potential data and thoracic cavity Tomography number
According to;
(2) the three-dimensional trunk geometric model of patient is set up respectively based on described thoracic cavity Tomography data
With three-dimensional cardiac geometric model, and then by three-dimensional trunk geometric model and three-dimensional cardiac geometric model at same seat
Mark aligned in spaces, obtains three-dimensional cardiac-human trunk model;
(3) body surface potential data of leading to described 64 carry out pretreatment, and the heart of ventricular premature contraction is occurring
Phase between dynamic cycle internal labeling QRS;
(4) obtain describing visceral pericardium electricity by calculating electrocardio direct problem according to described three-dimensional cardiac-human trunk model
The transformation matrix of mapping relations between position and body surface potential;Then according to this transformation matrix to labelling generation chamber
Body surface potential data in premature heart cycle carry out inverting and i.e. solve electrocardio inverse problem, reconstruct visceral pericardium electricity
Position distributed data, so the most sharp to exception according to electric excitation propagation of heart sequential chart and epicardial potential distributed data
Dynamic point is accurately positioned.
Described step (1) gathers the 64 of ventricular premature contraction patient and leads body surface potential data and break in thoracic cavity
Layer scanning imagery data, specific operation process is: first, makes patient be worn by 64 electrode leads are distributed
Body surface potential record waistcoat, lead body surface potential data gathering the 64 of patient;Then, by each on waistcoat
The wire of electrode takes out or cuts off, and continues the waistcoat remaining with electrode be worn on patient and make patient connect
By computed tomography, to obtain the thoracic cavity Tomography data of patient.
The process that implements setting up three-dimensional trunk geometric model in described step (2) is: first, pass through
It is imaged on handmarking in the tomoscan image of thoracic cavity and goes out the position of each electrode points to obtain the three-dimensional of each electrode points
Coordinate, and then the electrode points in three dimensions is carried out Delaunay Triangulation thus obtain the three-dimensional of patient
Trunk geometric model.
The process that implements setting up three-dimensional cardiac geometric model in described step (2) is: first, pass through
It is imaged in the tomoscan image of thoracic cavity the some sections intercepted on cardiac short axis direction: at least should comprise downwards
Apex of the heart position, upwards including at least right ventricular outflow position;Then, on above-mentioned cardiac short axis direction
Sectioning image is split, and respectively obtains visceral pericardium, the endocardial boundary profile of left endocardium and the right side;Finally,
Above-mentioned series of parallel boundary profile triangle gridding is connected, i.e. obtains three-dimensional cardiac geometric model.
Described step (2) being considered, digital image space and heart physiological space are on each orthogonal direction
Unit difference, it is therefore desirable to by three-dimensional trunk geometric model and three-dimensional cardiac geometric model at same coordinate space
Interior alignment, specifically according to DICOM (Digital Imaging and Communications in Medicine,
Digital imaging and communications in medicine) in critical field information to the size of three-dimensional cardiac geometric model and locus
It is corrected, the three-dimensional cardiac geometric model after correction is merged with three-dimensional trunk geometric model and i.e. obtains three-dimensional
Heart-human trunk model.
Body surface potential data of leading to 64 in described step (3) carry out pretreatment method particularly includes: first
First pass through filtering and the electric potential signal of each passage is carried out denoising;Then the method pair of fitting of a polynomial is used
Electric potential signal after each passage denoising is smoothed;The electrode institute that last Weeding state is bad
The electric potential signal of respective channel.
Body surface potential data in labelling generation chamber premature heart cycle are carried out instead by described step (4)
Drill, solve to reconstruct epicardial potential distributed data by following object function is optimized;
Wherein: H is to describe the transformation matrix of mapping relations between epicardial potential and body surface potential,Send out for labelling
Body surface potential data in raw ventricular premature contraction cardiac cycle,Epicardial potential data, λ is regularization parameter,
|| ||2Being two norms, L is unit matrix, gradient operator or Laplace operator.
The abnormal exciting independent positioning method of present invention ventricular premature contraction based on ECGI, leads body surface by setting up 64
The Collect jointly framework of potential data and Computed tomography, obtains the heart-human trunk model of personalization,
Solve electrocardio inverse problem by Tikhonov regularization, rebuild epicardial potential thus be accurately positioned ventricular premature contraction
The exciting point of exception, there is important actual application value.
Accompanying drawing explanation
Fig. 1 is the 64 crosslinking electrode distributing position schematic diagrams gathering body surface potential data.
Fig. 2 is the position view of each electrode in the tomoscan image of thoracic cavity.
Fig. 3 is personalized 3D human trunk model schematic diagram.
Fig. 4 is segmentation cardiac short axis picture centre adventitia, the signal of left endocardium and the right side endocardial boundary profile
Figure.
Fig. 5 is personalized 3D heart surface grid model schematic diagram.
Fig. 6 is the 3D heart-human trunk model schematic diagram after correction.
Detailed description of the invention
In order to describe the present invention the most clearly, below in conjunction with the accompanying drawings and the detailed description of the invention skill to the present invention
Art scheme is described in detail.
The abnormal exciting independent positioning method of present invention ventricular premature contraction based on ECGI, is embodied as step as follows:
S1. gather the 64 of ventricular premature contraction patient to lead body surface potential data and dress body surface potential record waistcoat
Thorax computer Tomography data.
The waistcoat making patient first dress 64 electrodes of distribution carries out body surface potential data record, and 64 lead at body
The distributing position of table is as shown in Figure 1;Then patient continues to wear this after taking out or cut short the wire on waistcoat
Waistcoat accepts computed tomography, record trunk and the geometry of heart.
S2. from computed tomography image, set up the 3D trunk geometric model of personalization.
64 electrode positions led in the tomoscan image of thoracic cavity are it is apparent that as in figure 2 it is shown, can be
Image space direct labor marks the position of electrode points;Then the three-dimensional coordinate of electrode points is obtained.Again to upper
State spatial discrete points carry out Delaunay trigonometric ratio thus obtain personalization 3D human trunk model, such as Fig. 3 institute
Show.
S3. from computed tomography image, set up the 3D heart geometric model of personalization.
First intercept the some sections on cardiac short axis direction, the most at least should comprise apex of the heart position, be upwardly into
Comprise right ventricular outflow position less;Then above-mentioned cardiac short axis image is split, respectively obtain outside the heart
Film, the endocardial boundary profile of left endocardium and the right side, as shown in Figure 4;Again by obtained in the previous step a series of
Parallel contours triangle gridding connects, and obtains the three-dimensional surface grid model of heart, as shown in Figure 5.
S4. human trunk model and heart model are alignd at the same space, obtain the heart-human trunk model of personalization.
The unit difference on each orthogonal direction in view of digital image space and heart physiological space, therefore needs
According to the critical field information in DICOM, size and the locus of 3D heart model are corrected,
3D heart-human trunk model after correction is as shown in Figure 6.
S5. body surface potential signal is carried out pretreatment, including denoising, smooth, labelling electrode and cycle etc..
First body surface potential signal is carried out denoising, conventional wave filter include Fourier Fast transforms,
Wavelet transformation and Butterworth wave filter etc.;Then the body surface potential data collected are smoothed
Purpose is to be withdrawn on same baseline by the signal of telecommunication.The method using fitting of a polynomial in present embodiment,
Polynomial order selects to obtain preferable result when 5 rank or 6 rank;Finally also need to labelling go to work
Make the electrode that state is bad, this electrode signal is foreclosed by the calculating below, also need to labelling simultaneously
Phase between the QRS of generation chamber premature heart cycle.
S6. according to the heart-human trunk model obtained in step S4, set up boundary element model and calculate electrocardio direct problem
Obtain describing the transformation matrix of mapping relations between epicardial potential and body surface potential.
Cardioelectric field can be regarded as quasi-electrostatic field, and assumes that human trunk model is uniform, the most each moment
Potential distribution can be expressed as at uniform, passive field region Laplace's equation:
Present embodiment utilizes Element BEM ask for the numerical solution of Laplace's equation, basic thought be by
Continuous print solves domain representation and becomes the combination of one group of discrete limited element, goes to approach with such combination and solves
Territory.The whole unknown field function solved on territory can be represented with approximate function in each unit, and approximate
Function is usually unknown field function and represents in unit interpolated value.Determine on assembly hence with interpolating function
Field function, thus the problem of continuous infinite degrees of freedom is converted into discrete finite degrees of freedom problem.Root
According to above-mentioned boundary element model, any point in model has:
Wherein: G is three-dimensional Green's function, q is source point to the distance between site.
At borderline integral equation it is:
Wherein, ci=1 θ/4 π, its implication is with boundary point as the centre of sphere, makees the least ball of a radius, this sphere with
Boundary face intersects, then θ is exactly the solid angle that i is opened by interface.Corresponding discrete form is:
Hypothetical boundary face S is broken down into z0Individual unit, each unit has the integration side of above-mentioned discrete form
Journey, the boundary element equation group being write as merging form is:
Transition matrix H can be tried to achieve by the formula elimination, it describe epicardial potential and body surface potential it
Between mapping relations.
S7. utilize transformation matrix that the body surface potential signal in the ventricular premature contraction cardiac cycle of labelling is carried out inverting,
Reconstruct epicardial potential distribution.
Assume the body surface potential of N number of pointEpicardial potential with M pointWherein meet N > M;
Relation between them can be expressed as by linear matrix:
Above-mentioned formula is ill, i.e. the eigenvalue of maximum of transition matrix H and the ratio of minimal eigenvalue are very big,
Can not directly invert, but solve minimum quadratic functional problem by being converted into, present embodiment uses
Tikhonov regularization method solves above-mentioned one-parameter minimization problem i.e.:
Wherein, λ is regularization parameter, characterizes the coefficient of balance between flatness and the fidelity solved;And operator L takes
The when of unit matrix I, the Tikhonov regularization of corresponding zeroth order;When L is gradient operator when, right
Answer the Tikhonov regularization of single order;When L is Laplace operator when, then it is second order Tikhonov
Regularization.The epicardial potential finally solved can be write as the following equivalent form of value:
S8. after reconstructing epicardial potential, according to electric excitation propagation of heart sequential chart to abnormal exciting point (high electricity
Position) it is accurately positioned.
Experiments verify that, computer running environment is: 8G internal memory, and CPU is intel i5, dominant frequency 3.47GHz;
Rebuild by above-mentioned implementation process and obtain epicardial potential and abnormal exciting point location result, abnormal exciting point minute
It is spaced after not being positioned at right ventricular outflow interventricular septum side and right ventricular outflow, this result and Ensite3000 system
Exciting some position of exception that system is measured by intrusive mood method in art is the most identical.
The above-mentioned description to embodiment is to be understood that for ease of those skilled in the art and apply
The present invention.Above-described embodiment obviously easily can be made various amendment by person skilled in the art,
And General Principle described herein is applied in other embodiments without through performing creative labour.Therefore,
The invention is not restricted to above-described embodiment, those skilled in the art, according to the announcement of the present invention, do for the present invention
The improvement and the amendment that go out all should be within protection scope of the present invention.
Claims (7)
1. the abnormal exciting independent positioning method of ventricular premature contraction based on ECGI, comprises the steps:
(1) gather the 64 of ventricular premature contraction patient to lead body surface potential data and thoracic cavity Tomography number
According to;
(2) the three-dimensional trunk geometric model of patient is set up respectively based on described thoracic cavity Tomography data
With three-dimensional cardiac geometric model, and then by three-dimensional trunk geometric model and three-dimensional cardiac geometric model at same seat
Mark aligned in spaces, obtains three-dimensional cardiac-human trunk model;
(3) body surface potential data of leading to described 64 carry out pretreatment, and the heart of ventricular premature contraction is occurring
Phase between dynamic cycle internal labeling QRS;
(4) obtain describing visceral pericardium electricity by calculating electrocardio direct problem according to described three-dimensional cardiac-human trunk model
The transformation matrix of mapping relations between position and body surface potential;Then according to this transformation matrix to labelling generation chamber
Body surface potential data in premature heart cycle carry out inverting and i.e. solve electrocardio inverse problem, reconstruct visceral pericardium electricity
Position distributed data, so the most sharp to exception according to electric excitation propagation of heart sequential chart and epicardial potential distributed data
Dynamic point is accurately positioned.
The abnormal exciting independent positioning method of ventricular premature contraction the most according to claim 1, it is characterised in that: institute
The step (1) stated gathers the 64 of ventricular premature contraction patient lead body surface potential data and thoracic cavity tomoscan
Imaging data, specific operation process is: first, makes patient be worn by being distributed the body surface of 64 electrode leads
Electrogram waistcoat, leads body surface potential data gathering the 64 of patient;Then, by electrode each on waistcoat
Wire takes out or cuts off, and continues the waistcoat remaining with electrode be worn on patient and make patient accept calculating
Machine tomoscan, to obtain the thoracic cavity Tomography data of patient.
The abnormal exciting independent positioning method of ventricular premature contraction the most according to claim 1, it is characterised in that: institute
The process that implements setting up three-dimensional trunk geometric model in the step (2) stated is: first, by being imaged on
In the tomoscan image of thoracic cavity, handmarking goes out the position three-dimensional coordinate with each electrode points of acquisition of each electrode points,
And then the electrode points in three dimensions carried out Delaunay Triangulation thus to obtain the three-dimensional trunk of patient several
What model.
The abnormal exciting independent positioning method of ventricular premature contraction the most according to claim 1, it is characterised in that: institute
The process that implements setting up three-dimensional cardiac geometric model in the step (2) stated is: first, by being imaged on
Thoracic cavity tomoscan image intercepts the some sections on cardiac short axis direction: at least should comprise apex of the heart position downwards
Put, upwards including at least right ventricular outflow position;Then, to the slice map on above-mentioned cardiac short axis direction
As splitting, respectively obtain visceral pericardium, the endocardial boundary profile of left endocardium and the right side;Finally, by upper
State series of parallel boundary profile triangle gridding to connect, i.e. obtain three-dimensional cardiac geometric model.
The abnormal exciting independent positioning method of ventricular premature contraction the most according to claim 1, it is characterised in that: institute
In the step (2) stated according to the critical field information in DICOM to the size of three-dimensional cardiac geometric model and
Locus is corrected, and is merged i.e. with three-dimensional trunk geometric model by the three-dimensional cardiac geometric model after correction
Obtain three-dimensional cardiac-human trunk model.
The abnormal exciting independent positioning method of ventricular premature contraction the most according to claim 1, it is characterised in that: institute
Body surface potential data of leading to 64 in the step (3) stated carry out pretreatment method particularly includes: first pass through
Filter the electric potential signal to each passage and carry out denoising;Then use the method for fitting of a polynomial to each passage
Electric potential signal after denoising is smoothed;Lead to corresponding to the electrode that last Weeding state is bad
The electric potential signal in road.
The abnormal exciting independent positioning method of ventricular premature contraction the most according to claim 1, it is characterised in that: institute
The step (4) stated carries out inverting to the body surface potential data in labelling generation chamber premature heart cycle, logical
Cross following object function is optimized and solve to reconstruct epicardial potential distributed data;
Wherein: H is to describe the transformation matrix of mapping relations between epicardial potential and body surface potential,Send out for labelling
Body surface potential data in raw ventricular premature contraction cardiac cycle,Epicardial potential data, λ is regularization parameter,
||||2Being two norms, L is unit matrix, gradient operator or Laplace operator.
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CN107007279A (en) * | 2017-03-17 | 2017-08-04 | 浙江大学 | A kind of noninvasive intracardiac exciting independent positioning method of exception based on stacking-type self-encoding encoder |
CN108324263A (en) * | 2018-01-11 | 2018-07-27 | 浙江大学 | A kind of noninvasive cardiac electrophysiology inversion method based on low-rank sparse constraint |
CN109091138A (en) * | 2018-07-12 | 2018-12-28 | 上海微创电生理医疗科技股份有限公司 | The judgment means and Mapping System of arrhythmia cordis originating point |
CN109452948A (en) * | 2017-09-06 | 2019-03-12 | 韦伯斯特生物官能(以色列)有限公司 | Mesh Fitting algorithm |
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CN110992461A (en) * | 2019-12-02 | 2020-04-10 | 哈尔滨工业大学 | Large-scale high-speed rotation equipment three-dimensional morphological filtering method based on unequal interval sampling |
CN112741634A (en) * | 2019-10-31 | 2021-05-04 | 清华大学深圳国际研究生院 | Heart focus positioning system |
WO2024018009A1 (en) * | 2022-07-20 | 2024-01-25 | Corify Care, S.L. | Methods to determine the morphology and the location of a heart within a torso |
Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20030018277A1 (en) * | 2001-07-19 | 2003-01-23 | Bin He | Method and apparatus of three dimension electrocardiographic imaging |
CN101002674A (en) * | 2007-01-16 | 2007-07-25 | 浙江大学 | Method for testing epicardium electrical potential combined with LSQR and hereditary calculation |
CN100562288C (en) * | 2008-04-18 | 2009-11-25 | 浙江大学 | Cardiac electric functional imaging method based on the beating heart model |
CN101991412A (en) * | 2010-11-09 | 2011-03-30 | 浙江大学 | Method for detecting heart surface transmural potential distribution |
EP2436909A1 (en) * | 2010-10-01 | 2012-04-04 | Continental Automotive GmbH | Valve assembly for an injection valve and injection valve |
CN103110417A (en) * | 2013-02-28 | 2013-05-22 | 华东师范大学 | Automatic electrocardiogram recognition system |
CN103961089A (en) * | 2014-05-27 | 2014-08-06 | 山东师范大学 | Sinus heart rate turbulence tendency detecting method based on segmented straight line fitting |
US9014795B1 (en) * | 2012-09-25 | 2015-04-21 | University Of South Florida | Systems and methods for determining a cardiovascular condition of a subject |
CN104825133A (en) * | 2015-05-04 | 2015-08-12 | 河南理工大学 | Colored Doppler 3D (three-dimensional) imaging based quasistatic ventricle-heart magnetic field model |
CN103202727B (en) * | 2012-01-12 | 2015-11-25 | 通用电气公司 | Non-invasive arrhythmia treatment system |
CN103829941B (en) * | 2014-01-14 | 2016-01-20 | 武汉培威医学科技有限公司 | A kind of multidimensional electrocardiosignal imaging system and method |
US20160113545A1 (en) * | 2014-10-23 | 2016-04-28 | Foundation Of Soongsil University-Industry Cooperation | System and method for analyzing electroencephalogram in response to image stimulus of media facade |
-
2016
- 2016-05-13 CN CN201610319277.XA patent/CN105796094B/en active Active
Patent Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20030018277A1 (en) * | 2001-07-19 | 2003-01-23 | Bin He | Method and apparatus of three dimension electrocardiographic imaging |
CN101002674A (en) * | 2007-01-16 | 2007-07-25 | 浙江大学 | Method for testing epicardium electrical potential combined with LSQR and hereditary calculation |
CN100562288C (en) * | 2008-04-18 | 2009-11-25 | 浙江大学 | Cardiac electric functional imaging method based on the beating heart model |
EP2436909A1 (en) * | 2010-10-01 | 2012-04-04 | Continental Automotive GmbH | Valve assembly for an injection valve and injection valve |
CN101991412A (en) * | 2010-11-09 | 2011-03-30 | 浙江大学 | Method for detecting heart surface transmural potential distribution |
CN103202727B (en) * | 2012-01-12 | 2015-11-25 | 通用电气公司 | Non-invasive arrhythmia treatment system |
US9014795B1 (en) * | 2012-09-25 | 2015-04-21 | University Of South Florida | Systems and methods for determining a cardiovascular condition of a subject |
CN103110417A (en) * | 2013-02-28 | 2013-05-22 | 华东师范大学 | Automatic electrocardiogram recognition system |
CN103829941B (en) * | 2014-01-14 | 2016-01-20 | 武汉培威医学科技有限公司 | A kind of multidimensional electrocardiosignal imaging system and method |
CN103961089A (en) * | 2014-05-27 | 2014-08-06 | 山东师范大学 | Sinus heart rate turbulence tendency detecting method based on segmented straight line fitting |
US20160113545A1 (en) * | 2014-10-23 | 2016-04-28 | Foundation Of Soongsil University-Industry Cooperation | System and method for analyzing electroencephalogram in response to image stimulus of media facade |
CN104825133A (en) * | 2015-05-04 | 2015-08-12 | 河南理工大学 | Colored Doppler 3D (three-dimensional) imaging based quasistatic ventricle-heart magnetic field model |
Non-Patent Citations (1)
Title |
---|
PENGCHENG SHI,HUAFENG LIU: "Stochastic finite element framework for simultaneous estimation of cardiac kinematic functions and material parameters", 《MEDICAL IMAGE ANALYSIS》 * |
Cited By (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107007279A (en) * | 2017-03-17 | 2017-08-04 | 浙江大学 | A kind of noninvasive intracardiac exciting independent positioning method of exception based on stacking-type self-encoding encoder |
CN107007279B (en) * | 2017-03-17 | 2019-11-05 | 浙江大学 | A kind of noninvasive intracardiac exciting independent positioning method of exception based on stacking-type self-encoding encoder |
CN109452948A (en) * | 2017-09-06 | 2019-03-12 | 韦伯斯特生物官能(以色列)有限公司 | Mesh Fitting algorithm |
CN109452948B (en) * | 2017-09-06 | 2024-04-09 | 韦伯斯特生物官能(以色列)有限公司 | Method and apparatus for grid fitting |
CN108324263A (en) * | 2018-01-11 | 2018-07-27 | 浙江大学 | A kind of noninvasive cardiac electrophysiology inversion method based on low-rank sparse constraint |
CN109091138A (en) * | 2018-07-12 | 2018-12-28 | 上海微创电生理医疗科技股份有限公司 | The judgment means and Mapping System of arrhythmia cordis originating point |
CN110393522A (en) * | 2019-06-28 | 2019-11-01 | 浙江大学 | A kind of noninvasive cardiac electrophysiology inversion method based on the constraint of figure total variation |
CN112741634A (en) * | 2019-10-31 | 2021-05-04 | 清华大学深圳国际研究生院 | Heart focus positioning system |
CN112741634B (en) * | 2019-10-31 | 2023-02-24 | 清华大学深圳国际研究生院 | Heart focus positioning system |
CN110992461A (en) * | 2019-12-02 | 2020-04-10 | 哈尔滨工业大学 | Large-scale high-speed rotation equipment three-dimensional morphological filtering method based on unequal interval sampling |
CN110946569A (en) * | 2019-12-24 | 2020-04-03 | 浙江省中医院 | Multichannel body surface electrocardiosignal synchronous real-time acquisition system |
WO2024018009A1 (en) * | 2022-07-20 | 2024-01-25 | Corify Care, S.L. | Methods to determine the morphology and the location of a heart within a torso |
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