CN105167849B - A kind of blood vessel three-dimensional path planning method based on ant group algorithm - Google Patents
A kind of blood vessel three-dimensional path planning method based on ant group algorithm Download PDFInfo
- Publication number
- CN105167849B CN105167849B CN201510255090.3A CN201510255090A CN105167849B CN 105167849 B CN105167849 B CN 105167849B CN 201510255090 A CN201510255090 A CN 201510255090A CN 105167849 B CN105167849 B CN 105167849B
- Authority
- CN
- China
- Prior art keywords
- ant
- pheromones
- blood vessel
- path
- maximum
- 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.)
- Expired - Fee Related
Links
- 210000004204 blood vessel Anatomy 0.000 title claims abstract description 48
- 238000000034 method Methods 0.000 title claims abstract description 36
- 239000003016 pheromone Substances 0.000 claims abstract description 60
- 238000011017 operating method Methods 0.000 claims abstract description 4
- 230000004087 circulation Effects 0.000 claims description 11
- 230000008859 change Effects 0.000 claims description 7
- 230000017531 blood circulation Effects 0.000 claims description 6
- 238000001704 evaporation Methods 0.000 claims description 6
- 230000008020 evaporation Effects 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 6
- 230000002792 vascular Effects 0.000 claims description 6
- 230000001351 cycling effect Effects 0.000 claims description 3
- 238000010586 diagram Methods 0.000 claims description 3
- 239000003814 drug Substances 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 3
- 230000008676 import Effects 0.000 claims description 3
- 230000006872 improvement Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 230000004048 modification Effects 0.000 claims description 2
- 238000012986 modification Methods 0.000 claims description 2
- 230000037361 pathway Effects 0.000 abstract description 2
- 238000001356 surgical procedure Methods 0.000 abstract description 2
- 241000257303 Hymenoptera Species 0.000 description 5
- 229920003266 Leaf® Polymers 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 5
- 238000005452 bending Methods 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 239000008280 blood Substances 0.000 description 2
- 210000004369 blood Anatomy 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 208000035965 Postoperative Complications Diseases 0.000 description 1
- 230000000740 bleeding effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000002059 diagnostic imaging Methods 0.000 description 1
- 230000003902 lesion Effects 0.000 description 1
- 230000001394 metastastic effect Effects 0.000 description 1
- 206010061289 metastatic neoplasm Diseases 0.000 description 1
- 235000001968 nicotinic acid Nutrition 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 208000019553 vascular disease Diseases 0.000 description 1
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Infusion, Injection, And Reservoir Apparatuses (AREA)
Abstract
The invention discloses a kind of blood vessel three-dimensional path planning method based on ant group algorithm, the operating procedure of this method is as follows：Vessel centerline network topology structure, 5 ant reconnaissance algorithms, 6 parameter initializations, the calculating of 7 heuristic informations, the volatilization of 8 probability selections, 9 pheromones dynamic, 10 pheromones incremental computations, 11 Pheromone updates, 12 planning end judgements, the output of 13 results are set up in the importing of 1 data, the modeling of 2 blood vessels, 3 blood vessel center line drawings, 4.This method uses ant reconnaissance algorithms on the basis of heart line drawing in the blood vessel, by improving ant group algorithm, and considers conduit diameter, length of vessel, minimum diameter, maximum curvature and the optimal path of maximum torsion assisted surgery doctor planning operation.This method puies forward the reliability of the preoperative path planning of blood vessel intervention operation, it is ensured that conduit by property, a kind of new operation pathway normative reference can be provided for surgeon.
Description
Technical field
The present invention relates to a kind of blood vessel three-dimensional path planning method based on ant group algorithm, belong to blood vessel three-dimensional path
Planning technology field.
Background technology
Blood vessel intervention operation has bleeding few, and wound is small, recovers fast advantage, therefore obtained in the treatment of vascular diseases
Extensive use.The blood vessel intervention operation of the most of hospital in the whole nation still by surgeon's hand operation catheter guide wire and is borrowed at present
The computer aided techniques such as the medical imaging technologies such as X-ray and virtual reality are helped to complete operation.Under limited technical conditions, from
The factors such as the operation level of doctor, danger, the postoperative complications performed the operation consider, thicker sustainer conduct is generally selected in art
Operation pathway, other possible optimal paths are not considered.
Blood vessel three-dimensional path planning is in three-dimensional geometry space, to find one from operative incision to lesions position
Optimal path, is a kind of Global motion planning problem, is the important means of preoperative planning.The key technology of intravascular three-dimensional path planning
It is the extraction of vessel centerline and the planning of guidance path.Extracting the method for center line has topological thinning method, range conversion method, gesture
Can field method, method based on level set method and based on segmentation etc..In terms of navigation path planning, with the rise of intelligent algorithm, have
Scholar searches the shortest path between 2 points using dijkstra's algorithm and A star algorithms in the vessel centerline of extraction.But
Other characteristics of these methods in planning process not in view of blood vessel.
Ant group algorithm is one of Swarm Intelligence Algorithm in bionics, and it is 1991 by Italian scholar M.Dorigo et al.
Proposed by after the inspiration of the behavior of Food Recruiment In Ants in real world.It is residual that algorithm core is that ant can be chosen with higher probability
Pheromone concentration highest path is stayed, increasing ant can be attracted on this paths, form a kind of positive feedback principle
To find one from food source most short path.The three-dimensional path planning based on ant group algorithm is concentrated mainly on nothing both at home and abroad at present
In terms of man-machine, submersible, three-dimensional tube, robot, temporary no document applies ant group algorithm in blood vessel three-dimensional path planning
Aspect.
The content of the invention
The problem of it is an object of the invention to exist for existing blood flow paths planning technology and deficiency are based on there is provided one kind
The three-dimensional path planning method of ant group algorithm, this method uses ant reconnaissance algorithms on the basis of heart line drawing in the blood vessel, leads to
Improvement ant group algorithm is crossed, and considers conduit diameter, length of vessel, diameter, curvature and torsion assisted surgery doctor planning hand
The optimal path of art.
To reach above-mentioned purpose, idea of the invention is that：Blood vessel modeling is carried out to CTA medical image datas and center is extracted
Line, ant reconnaissance algorithms are used in the vessel centerline network of given starting point on this basis, by improving ant group algorithm,
Composite catheter diameter and blood vessel other characteristics, such as length of vessel, minimum diameter, maximum curvature and maximum torsion factor carry out global
Path planning.
According to the design of the present invention, the present invention is realized using following technical scheme：
A kind of blood vessel three-dimensional path planning method based on ant group algorithm, it is characterised in that operating procedure is as follows：1 data are led
Enter, the modeling of 2 blood vessels, 3 blood vessel center line drawings, 4 set up vessel centerline network topology structure, 5 ant reconnaissance algorithms, 6 parameters
Initialization, the calculating of 7 heuristic informations, the volatilization of 8 probability selections, 9 pheromones dynamic, 10 pheromones incremental computations, 11 pheromones are more
Newly, 12 planning terminate judgement, the output of 13 results.
Step 1 data are imported：Import one group of complete medicine CT A view data (DICOM)；
The step 2 blood vessel modeling：The CTA view data of importing is carried out into blood vessel using the method based on 3D level sets to build
Mould；
The step 3 blood vessel center line drawing：The vascular pattern of foundation is used and is based on Voronoi diagram and Eikonal side
The method of journey extracts vessel centerline, and tries to achieve maximum inscribe radius of a ball R；
The step 4 sets up vessel centerline network topology structure：Network topology knot is set up according to central line pick-up result
Structure, determines the quantity on node and side, and calculates distance, maximum curvature, maximum torsion and the minimum diameter in each section of path；
4-1 distances are calculated, and the length of space curve is calculated using first form curve integral.Assuming that the sky of parameterized form
Half interval contour equation is
Therefore the range formula of space curve can be obtained is：
4-2 maximum curvatures are calculated, and curvature (curvature) is aiming at the tangent directional angle that some is put on curve to arc length
Rotation rate calculate the curvature of each point curve on center line, center curvature of a curve reflects the degree of vascular bending, and curvature
More big then vascular bending degree is bigger, will increase the difficulty that conduit passes through, and reduces the passability of blood vessel.For parametrization shape
The curvature estimation of formula space curve equation is：
The curvature each put on the path is calculated according to this formula and the maximum curvature C in the path is tried to achievemax；
4-3 maximum torsions are calculated, on the absolute value measure of torsion (torsion) curve neighbouring 2 points secondary normal vector it
Between angle to the rate of change of arc length, the torsion on center line can reflect the degree of buckling of vessel, for basin endoluminal vascular
Degreeof tortuosity be that than larger, and the bigger buckling of vessel degree of torsion is bigger, will also increase the difficulty that conduit passes through, and reduces blood
Pipe passability, reduces safety coefficient.Torsion for parameterized form space curve equation is calculated as：
The torsion each put on the path is calculated according to this formula and the maximum torsion T in the path is tried to achievemax；
4-4 minimum diameters are calculated, and the diameter D each put on center line can be calculated according to maximum inscribe radius of a ball R, is thus counted
Calculate the minimum diameter D on each pathmin, it is assumed that a diameter of D of surgical cathetersc, it is desirable to the minimum diameter D of this section of blood flow pathsmin
＞ DcTo ensure that conduit can pass through blood vessel；
The step 5 ant reconnaissance algorithms：Starting point is determined, the ant reconnaissance algorithms with self-replacation function are performed.
Because blood vessel network topological structure is not that loop is not present between a complete graph, some nodes, one is certainly existed
A little leafs.If ant is in search process, when having gone to a leaf and not terminal, otherwise pathfinding is just directly exited,
The upper node for just returning to leaf continues pathfinding.If selecting the former, although can accelerate convergence, but the shortcoming overall situation is examined
Consider, exit too early；If selecting the latter, although from overall situation consideration, but efficiency of algorithm can be reduced.Therefore, the present invention is it is determined that starting
After point, allow ant first to be scouted to whole network topological structure, distinguish and perform ant again after removing this kind of non-terminal leaf
Group's algorithm.This kind of scouting ant possesses self-replacation function, during scouting can according to summit V number of degrees N, i.e. side number,
Corresponding self-replacation (in addition to the side accessed), then respectively toward the continuation scouting of other summits.
5-1 places the ant Mv=Nv, Mu=Nu of respective amount according to starting point v and terminal the u number of degrees respectively；
Every ant of 5-2 scouts summit ViWhen be first saved to respective routing table TaiIn, do scouting mark；
Every ant of 5-3 judges the summit V scoutediNumber of degrees Ni,
If 5-3-1 n ≠ 1, n-2 ant copy is replicated, continues to scout；
If 5-3-2 n=1, summit V is reportediFor abnormity point, the point is rejected, a summit V thereon is changedi-1The number of degrees
Ni-1, overall network topology structure is updated, into step 5-4；
5-4 is according to routing table TaiA summit V is returned to along former roadi-1If n=1 performs step 5-3-2；If n ≠
1, then into step 5-5；
If 5-5 has been scouted on all summits, terminate and scout, into parameter initialization 6；Otherwise step 5-3 is entered；
Step 6 parameter initialization：Each parameter is initialized, ant quantity M, pheromones intensity constant Q, iteration are such as set
Sum, conduit diameter Dc, ant is placed in initial position；
Step 7 heuristic information is calculated：Heuristic function has important shadow to convergence and stability
Ring, in ant group algorithm, heuristic information η is usually the inverse ratio of distance between two points, i.e. 1/LI, J, path planning of the present invention
Standard is that operation safety and path are optimal, therefore the length L of blood vessel is not only considered in path planningI, J, maximum curvature Cmax
With maximum torsion Tmax, it is contemplated that the minimum diameter D of blood vesselmin, heuristic information is defined as
ηI, J(t) represent that t node I (x, y, z) arrives node J (x ', y ', z ') heuristic information；X, y, z and x ', y ',
Z ' is the three-dimensional coordinate of point；DminRepresent the minimum diameter of this paths, DcRepresent conduit diameter, it is desirable to Dmin＞ Dc；LI, JRepresent
This path length；CmaxRepresent the maximum curvature in this section of path, Tmax, represent the maximum torsion in this section of path.
Step 8 probability selection：Provided with M ant, n node, ai(t) represent that t is located at certain node I ant
Quantity, thenIn each step Path selection of ant group algorithm, ant m according to probability determine next step toward which
Bar is moved on road.
Represent that t ant m is moved to point J probability, allowed by point Im={ 1,2 ..., n }-tmTable
Show the node that ant next step can be selected, tmRepresent the node that ant once accessed；α represents pheromones heuristic factor, table
Show residual risk element amount the role of when ant move, value is bigger to illustrate that ant is more likely to select other ants processes
Collaboration capabilities between path, ant are stronger；β represents desired value heuristic factor, shows heuristic information when ant selects path
By attention degree, be worth bigger, state metastatic rule is closer to greedy rule.τI, J(t) represent t point I to point J paths
Pheromones.
Step 9 pheromones are dynamically volatilized：Pheromones evaporation rate can be over time by temperature, humidity etc.
Factor and change, be a process dynamically changed, more complicated path, heuristic information is smaller, evaporation rate is faster, information
Element residual it is fewer, therefore pheromones volatility coefficient ρ with heuristic information ηI, J(t) change and dynamic is volatilized, all ants
After reaching home, calculated by following relation,
ρI, J(t) volatility coefficient of the t on I to J paths, η are representedI, J(t) information on t I to J paths is represented
Element,The heuristic information on all paths of t is represented, k represents certain ant in t paths traversed number.
The step 10 pheromones incremental computations：Pheromone update model be Basic Ant Group of Algorithm random search with it is quick
Restrain important step.The optimum of overall situation requirement of the present invention for problem in itself, using all models of ant；It is minimum straight in view of blood vessel
The influence of footpath and conduit diameter in operation, all models of modification ant are as follows：
Q is pheromones intensity constant, is the total of the pheromones that ant discharges in paths traversed in a cycle
Amount, affects convergence of algorithm speed to a certain extent；It is required that the minimum diameter D of blood flow pathsmin＞ Dc, LmRepresent m only
Ant paths traversed length in this circulation, according to every ant in its routing table TamIn result calculate.
Step 11 Pheromone update：Pheromones amount on each path of initial time is equal, when ant completes one
After secondary circulation, pheromones can gradually volatilize over time, therefore pheromone concentration will be updated, and enter in ant
Following renewal is done to the pheromones in respective paths before entering next circulation：
τI, J(t+1)=(1- ρ) τI, J(t)+ΔτI, J(t, t+1)
ρ (O ＜ ρ ＜ 1) is the dynamic volatility coefficient of pheromones, and 1- ρ are the pheromones dynamically residual factors,Table
Show the pheromones amount that the m ant leaves in this circulation on path (I, J), Δ τI, J(t, t+1) represents that this circulation is worked as
In the pheromones increment that leaves of all ants by path (I, J).
Step 12 planning terminates to judge：When reaching that maximum iteration then exits circulation, otherwise enter heuristic letter
Breath calculates 7, continues cycling through；
The step 13 result output：Arrange routing table output result.
The present invention compared with prior art, substantive distinguishing features and remarkable advantage is obviously protruded with following：
(1) ant group algorithm is applied to blood vessel three-dimensional path planning technical field by the present invention.
(2) present invention improves over the heuristic information model in ant group algorithm, conduit diameter, blood vessel have been considered long
Degree, minimum diameter, maximum curvature and maximum torsion, improve the reliability of preoperative path planning, it is ensured that conduit passes through property.
(3) present invention improves over the pheromones incremental model in ant group algorithm, combine blood vessel minimum diameter and conduit is straight
Influence of the footpath in planning, accelerates convergence of algorithm.
Brief description of the drawings
Fig. 1 is a kind of flow chart of the blood vessel three-dimensional path planning method based on ant group algorithm of the present invention.
Embodiment
Embodiments of the present invention are described in further detail below in conjunction with the accompanying drawings.
Embodiment one：
Referring to Fig. 1, a kind of blood vessel three-dimensional path planning method based on ant group algorithm, it is characterised in that operating procedure is such as
Under, the importing of 1 data, the modeling of 2 blood vessels, 3 blood vessel center line drawings, 4 are set up vessel centerline network topology structure, 5 ants and scouted
Algorithm, 6 parameter initializations, the calculating of 7 heuristic informations, 8 probability selections, 9 pheromones dynamic volatilization, 10 pheromones incremental computations,
11 Pheromone updates, 12 planning terminate judgement, the output of 13 results.
Step 1 data are imported：Import one group of complete medicine CT A view data (DICOM)；
The step 2 blood vessel modeling：The CTA view data of importing is carried out into blood vessel using the method based on 3D level sets to build
Mould；
The step 3 blood vessel center line drawing：The vascular pattern of foundation is used and is based on Voronoi diagram and Eikonal side
The method of journey extracts vessel centerline, and tries to achieve maximum inscribe radius of a ball R；
The step 4 sets up vessel centerline network topology structure：Network topology knot is set up according to central line pick-up result
Structure, determines the quantity on node and side, and calculates distance, maximum curvature, maximum torsion and the minimum diameter in each section of path；
4-1 distances are calculated, and the length of space curve is calculated using first form curve integral；
4-2 maximum curvatures are calculated, and are calculated according to the curvature estimation formula of parameterized form space curve equation on the path
The curvature each put and the maximum curvature C for trying to achieve the pathmax；
4-3 maximum torsions are calculated, and are calculated according to the torsion calculation formula of parameterized form space curve equation on the path
The torsion each put and the maximum torsion T for trying to achieve the pathmax；
4-4 minimum diameters are calculated, and the diameter D each put on center line is calculated according to maximum inscribe radius of a ball R, is thus calculated
Minimum diameter D on each pathmin, it is assumed that a diameter of D of surgical cathetersc, then the minimum diameter D of this section of blood flow paths is requiredmin
＞ DcTo ensure that conduit can pass through blood vessel.
The step 5 ant reconnaissance algorithms：It is determined that after starting point, allowing ant first to be detectd to whole network topological structure
Examine, distinguish and perform ant group algorithm again after removing this kind of non-terminal leaf.This kind of scouting ant possesses self-replacation function,
Can be according to summit V number of degrees N, i.e. side number, corresponding self-replacation (in addition to the side accessed), then distinguish during scouting
Continue to scout toward other summits；
5-1 places the ant Mv=Nv, Mu=Nu of respective amount according to starting point v and terminal the u number of degrees respectively；
5-2 selects a summit V from vertex set Vi, judge summit ViWhether scout；
If 5-2-1 ViDo not scout, then every ant scouts summit ViWhen be first saved to respective routing table TajIn,
Do scouting mark；
If 5-2-2 ViIt has been scouted that, then return to 5-2；
Every ant of 5-3 judges the summit V scoutediNumber of degrees Ni,
If 5-3-1 n ≠ 1, n-2 ant copy is replicated, continues to scout；
If 5-3-2 n=1, summit V is reportediFor abnormity point, the point is rejected, a summit V thereon is changedi-1The number of degrees
Ni-1, overall network topology structure is updated, into step 5-4；
5-4 is according to routing table TaiA summit V is returned to along former roadi-1If n=1 performs step 5-3-2；If n ≠
1, then into step 5-5；
If 5-5 has been scouted on all summits, terminate and scout, into parameter initialization 6；Otherwise step 5-3 is entered；
Step 6 parameter initialization：Each parameter is initialized, ant quantity M, pheromones intensity constant Q, iteration are such as set
Sum, conduit diameter Dc, ant is placed in initial position.
Embodiment two：The present embodiment and embodiment one are essentially identical, and special feature is as follows：
Step 7 heuristic information is calculated：The standard of path planning of the present invention is that operation safety and path are optimal, therefore
The length L of blood vessel is not only considered in path planningI, J, maximum curvature CmaxWith maximum torsion Tmax, it is contemplated that blood vessel
Minimum diameter Dmin；
Step 8 probability selection：In each step Path selection of ant group algorithm, ant m according to new probability formula ratio
Rate determines next step toward moving on which bar road；
Step 9 pheromones are dynamically volatilized：Pheromones evaporation rate can be over time by temperature, humidity etc.
Factor and change, be a process dynamically changed, more complicated path, heuristic information is smaller, evaporation rate is faster, information
Element residual it is fewer, therefore pheromones volatility coefficient ρ with heuristic information ηI, J(t) change and dynamic is volatilized.
Embodiment three：The present embodiment and embodiment two are essentially identical, and special feature is as follows：
The step 10 pheromones incremental computations：Pheromone update model be Basic Ant Group of Algorithm random search with it is quick
Restrain important step.The optimum of overall situation requirement of the present invention for problem in itself, using all models of ant；It is minimum straight in view of blood vessel
The influence of footpath and conduit diameter in operation, is calculated according to pheromones incremental model after improvement；
Step 11 Pheromone update：Pheromones amount on each path of initial time is equal, when ant completes one
After secondary circulation, pheromones can gradually volatilize over time, therefore pheromone concentration will be updated, and enter in ant
Corresponding renewal is done to the pheromones in respective paths before entering next circulation；
Step 12 planning terminates to judge：When reaching that maximum iteration then exits circulation, otherwise enter heuristic letter
Breath calculates 7, continues cycling through；
The step 13 result output：Arrange routing table output result.
Claims (4)
1. a kind of blood vessel three-dimensional path planning method based on ant group algorithm, it is characterised in that operating procedure is as follows：1 data are led
Enter, the modeling of 2 blood vessels, 3 blood vessel center line drawings, 4 set up vessel centerline network topology structure, 5 ant reconnaissance algorithms, 6 parameters
Initialization, the calculating of 7 heuristic informations, the volatilization of 8 probability selections, 9 pheromones dynamic, 10 pheromones incremental computations, 11 pheromones are more
Newly, 12 planning terminate judgement, the output of 13 results；
Step 1 data are imported：Import one group of complete medicine CT A view data；
The step 2 blood vessel modeling：The CTA view data of importing is subjected to blood vessel modeling using the method based on 3D level sets；
The step 3 blood vessel center line drawing：The vascular pattern of foundation is used based on Voronoi diagram and Eikonal equations
Method extracts vessel centerline, and tries to achieve maximum inscribe radius of a ball R；
The step 4 sets up vessel centerline network topology structure：Network topology structure is set up according to central line pick-up result, really
Determine the quantity on node and side, and calculate distance, maximum curvature, maximum torsion and the minimum diameter in each section of path；
4-1 distances are calculated, and the length of space curve is calculated using first form curve integral；
4-2 maximum curvatures are calculated, and calculate each on the path according to the curvature estimation formula of parameterized form space curve equation
The curvature of point and the maximum curvature C for trying to achieve the pathmax；
4-3 maximum torsions are calculated, and calculate each on the path according to the torsion calculation formula of parameterized form space curve equation
The torsion of point and the maximum torsion T for trying to achieve the pathmax；
4-4 minimum diameters are calculated, and the diameter D each put on center line is calculated according to maximum inscribe radius of a ball R, each road is thus calculated
Minimum diameter D on footpathmin, it is assumed that a diameter of D of surgical cathetersc, then the minimum diameter D of this section of blood flow paths is requiredmin＞ DcWith
Ensure that conduit can pass through blood vessel；
The step 5 ant reconnaissance algorithms：It is determined that after starting point, allow ant first to be scouted to whole network topological structure,
Distinguish and perform ant group algorithm again after removing this kind of non-terminal leaf；This kind of scouting ant possesses self-replacation function, is detecing
Can be according to summit V number of degrees N, i.e. side number, corresponding self-replacation during examining, then continue toward other summits to scout respectively；
5-1 places the ant Mv=Nv, Mu=Nu of respective amount according to starting point v and terminal the u number of degrees respectively；
5-2 selects a summit V from vertex set Vi, judge summit ViWhether scout；
If 5-2-1 ViDo not scout, then every ant scouts summit ViWhen be first saved to respective routing table TaiIn, detect
Examine mark；
If 5-2-2 ViIt has been scouted that, then return to 5-2；
Every ant of 5-3 judges the summit V scoutediNumber of degrees Ni,
If 5-3-1 n ≠ 1, n-2 ant copy is replicated, continues to scout；
If 5-3-2 n=1, summit V is reportediFor abnormity point, the point is rejected, a summit V thereon is changedi-1Number of degrees Ni-1, more
New overall network topology structure, into step 5-4；
5-4 is according to routing table TaiA summit V is returned to along former roadi-1If n=1 performs step 5-3-2；If n ≠ 1, enter
Enter step 5-5；
If 5-5 has been scouted on all summits, terminate and scout, into parameter initialization 6；Otherwise step 5-3 is entered；
Step 6 parameter initialization：Each parameter is initialized, ant quantity M is such as set, pheromones intensity constant Q, iteration is total
Number, conduit diameter Dc, ant is placed in initial position；
Step 7 heuristic information is calculated：The standard of this path planning is that operation safety and path are optimal, therefore path planning
In not only will consider blood vessel length LI, J, maximum curvature CmaxWith maximum torsion Tmax, it is contemplated that the minimum diameter of blood vessel
Dmin；
The step 10 pheromones incremental computations：Pheromone update model is the random search and Fast Convergent of Basic Ant Group of Algorithm
Important step；For the optimum of overall situation requirement of problem in itself, using all models of ant；It is straight in view of blood vessel minimum diameter and conduit
Influence of the footpath in operation, is calculated according to pheromones incremental model after improvement, and all models of modification ant are as follows：
Q is pheromones intensity constant, is the total amount for the pheromones that ant discharges in paths traversed in a cycle,
Convergence of algorithm speed is affected to a certain extent；It is required that the minimum diameter D of blood flow pathsmin＞ Dc, LmRepresent that the m ant exists
Paths traversed length in this time circulating, according to every ant in its routing table TamIn result calculate.
2. the blood vessel three-dimensional path planning method according to claim 1 based on ant group algorithm, it is characterised in that the step
Rapid 8 probability selection：In each step Path selection of ant group algorithm, ant m determines that next step is past according to the ratio of new probability formula
Any moved on bar road.
3. the blood vessel three-dimensional path planning method according to claim 1 based on ant group algorithm, it is characterised in that the step
Rapid 9 pheromones are dynamically volatilized：Pheromones evaporation rate can over time by temperature, humidity factor and change, be one
The individual process dynamically changed, more complicated path, heuristic information is smaller, and evaporation rate is faster, and pheromones residual is fewer, therefore
The volatility coefficient ρ of pheromones is with heuristic information ηI, J(t) change and dynamic is volatilized.
4. the blood vessel three-dimensional path planning method according to claim 1 based on ant group algorithm, it is characterised in that the step
Rapid 11 Pheromone update：Pheromones amount on each path of initial time is equal, after ant completes one cycle, pheromones
It can gradually volatilize, therefore pheromone concentration will be updated over time, enter next circulation in ant
The preceding pheromones in respective paths do corresponding renewal；
Step 12 planning terminates to judge：When reaching that maximum iteration then exits circulation, otherwise into heuristic information meter
7 are calculated, is continued cycling through；
The step 13 result output：Arrange routing table output result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510255090.3A CN105167849B (en) | 2015-05-19 | 2015-05-19 | A kind of blood vessel three-dimensional path planning method based on ant group algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510255090.3A CN105167849B (en) | 2015-05-19 | 2015-05-19 | A kind of blood vessel three-dimensional path planning method based on ant group algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105167849A CN105167849A (en) | 2015-12-23 |
| CN105167849B true CN105167849B (en) | 2017-07-25 |
Family
ID=54890646
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510255090.3A Expired - Fee Related CN105167849B (en) | 2015-05-19 | 2015-05-19 | A kind of blood vessel three-dimensional path planning method based on ant group algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105167849B (en) |
Families Citing this family (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ES2973208T3 (en) * | 2016-02-16 | 2024-06-19 | Mentice Ab | Systems for routing a catheter into a vessel |
| CN107397588B (en) * | 2016-05-20 | 2020-03-06 | 中国科学院深圳先进技术研究院 | Simulation method and device for interventional embolization operation process |
| CN116051580A (en) * | 2017-05-09 | 2023-05-02 | 上海联影医疗科技股份有限公司 | Blood vessel separation method and system |
| CN109902391B (en) * | 2018-11-27 | 2023-10-17 | 中国石油大学(华东) | Oil gas pipeline planning method based on random volatilization coefficient ant colony algorithm |
| CN110604616B (en) * | 2019-09-10 | 2020-12-11 | 中国科学院深圳先进技术研究院 | Interventional operation path planning method and system based on graph search and electronic equipment |
| CN110706272B (en) * | 2019-10-17 | 2022-03-29 | 上海微创卜算子医疗科技有限公司 | Blood vessel centerline extraction method and device, electronic equipment and storage medium |
| CN113081257B (en) * | 2019-12-23 | 2022-06-07 | 四川医枢科技股份有限公司 | Automatic planning method for operation path |
| CN113116521A (en) * | 2019-12-31 | 2021-07-16 | 杭州堃博生物科技有限公司 | Operation indication method, medium, terminal device and system |
| CN113496541B (en) * | 2020-03-20 | 2024-07-09 | 中国科学院沈阳计算技术研究所有限公司 | Method for constructing three-dimensional model of blood vessel |
| CN112700551A (en) * | 2020-12-31 | 2021-04-23 | 青岛海信医疗设备股份有限公司 | Virtual choledochoscope interventional operation planning method, device, equipment and storage medium |
| CN113485353B (en) * | 2021-07-23 | 2024-03-15 | 江南大学 | Micro-robot obstacle avoidance method based on combination of RRT algorithm and artificial potential field method |
| CN114027984B (en) * | 2022-01-06 | 2022-03-11 | 极限人工智能有限公司 | Tortuous blood vessel crossing control device and vascular robot system |
| CN115148344B (en) * | 2022-09-06 | 2022-11-29 | 深圳市指南针医疗科技有限公司 | Ant colony algorithm-based medical and technical management method, device, equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003101300A2 (en) * | 2002-06-04 | 2003-12-11 | Koninklijke Philips Electronics N.V. | Rotational angiography based hybrid 3-d reconstruction of coronary arterial structure |
| CN101283929A (en) * | 2008-06-05 | 2008-10-15 | 华北电力大学 | Rebuilding method of blood vessel three-dimensional model |
| CN103472828A (en) * | 2013-09-13 | 2013-12-25 | 桂林电子科技大学 | Mobile robot path planning method based on improvement of ant colony algorithm and particle swarm optimization |
| US20140254906A1 (en) * | 2013-03-11 | 2014-09-11 | Toshiba Medical Systems Corporation | Vascular tree from anatomical landmarks and a clinical ontology |
-
2015
- 2015-05-19 CN CN201510255090.3A patent/CN105167849B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003101300A2 (en) * | 2002-06-04 | 2003-12-11 | Koninklijke Philips Electronics N.V. | Rotational angiography based hybrid 3-d reconstruction of coronary arterial structure |
| CN101283929A (en) * | 2008-06-05 | 2008-10-15 | 华北电力大学 | Rebuilding method of blood vessel three-dimensional model |
| US20140254906A1 (en) * | 2013-03-11 | 2014-09-11 | Toshiba Medical Systems Corporation | Vascular tree from anatomical landmarks and a clinical ontology |
| CN103472828A (en) * | 2013-09-13 | 2013-12-25 | 桂林电子科技大学 | Mobile robot path planning method based on improvement of ant colony algorithm and particle swarm optimization |
Non-Patent Citations (3)
| Title |
|---|
| 一种障碍环境下机器人路径规划的蚁群粒子群算法;邓高峰等;《控制理论与应用》;20090815;第26卷(第8期);879-883 * |
| 基于惯性蚁群算法的机器人路径规划;何少佳等;《计算机工程与应用》;20120406;第48卷(第15期);246-248 * |
| 基于蚁群算法的机器人路径规划;张美玉等;《计算机工程与应用》;20050901(第25期);34-37 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105167849A (en) | 2015-12-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105167849B (en) | A kind of blood vessel three-dimensional path planning method based on ant group algorithm | |
| US7379062B2 (en) | Method for determining a path along a biological object with a lumen | |
| KR20190047073A (en) | Systems and methods for estimation of blood flow characteristics using reduced order models and machine learning | |
| CN110638438B (en) | Method and system for machine learning based assessment of fractional flow reserve | |
| US7371067B2 (en) | Simulation method for designing customized medical devices | |
| CN111429438B (en) | Method, apparatus and storage medium for extracting blood vessel center line and heart coronary tree | |
| US10235753B2 (en) | Automatic recognition of anatomical landmarks | |
| WO2022199403A1 (en) | Blood vessel centerline extraction method and apparatus | |
| US20060270927A1 (en) | Preoperative and intra-operative imaging-based procedure workflow with complexity scoring | |
| CN108961273B (en) | Method and system for segmenting pulmonary artery and pulmonary vein from CT image | |
| JP2011525827A (en) | Nested cannula for minimally invasive surgery | |
| CN112254733B (en) | Fire escape path planning method and system based on extended A-x algorithm | |
| JP2022512528A (en) | Methods, devices, and devices for simulating the path of catheter movement within a blood vessel | |
| JP2019177135A (en) | Automatic identification of multiple activation pathways | |
| WO2024149161A1 (en) | Catheter robot and registration method therefor, and readable storage medium | |
| CN107392891B (en) | Blood vessel tree extraction method, device, equipment and storage medium | |
| CN114926700B (en) | Coronary artery type determination method, device, electronic device and storage medium | |
| JP2023552577A (en) | Dynamic deformation tracking for navigational bronchoscopy | |
| CN109003283A (en) | A kind of aorta outline segmentation based on active shape model | |
| CN109414187A (en) | Catheter type selection | |
| Bruyninckx et al. | Segmentation of liver portal veins by global optimization | |
| CN113876420A (en) | Path planning method, system, device and medium for planning surgical path | |
| CN111897857A (en) | ICU (intensive care unit) duration prediction method after aortic dissection cardiac surgery | |
| US9387047B2 (en) | Interstital lung access using nested cannulas | |
| CN111242915A (en) | Blood vessel 3D/2D registration method and device based on Monte Carlo tree search |
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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170725 |