CN107185117A - Towards the sigmatron zone routing optimization method of multiple tumor radiotherapy - Google Patents
Towards the sigmatron zone routing optimization method of multiple tumor radiotherapy Download PDFInfo
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Abstract
The present invention belongs to Medical Devices and field of artificial intelligence towards the sigmatron zone routing optimization method of multiple tumor radiotherapy；Actual tumor region is degenerated to actual tumour point by this method first, it is determined that the coordinate of actual tumour point；Then the distance between actual tumour point of any two is calculated, distance matrix is set up；Reinitialize exploration parameter, calculates heuristic function initial value；Then optimal loop path is explored；Two maximum actual tumour points of distance in optimal loop path are eventually found, the line of described two actual tumour points is removed in optimal loop path, and remainder is final path；Actual tumor region is degenerated to a tumour point by the present invention, radiological scans problem is converted to and how to travel through all tumour points and shortest path problem, and propose a kind of method for optimizing route, substantially reduce treatment time, mitigate Case treatment pain, positive facilitation will be played to development of the artificial intelligence in Medical Devices.
Description
Technical field
The present invention towards multiple tumor radiotherapy sigmatron zone routing optimization method belong to Medical Devices and
Field of artificial intelligence.
Background technology
Tumour radiotherapy is a kind of local therapeutic approaches using radiation cure tumour.It is same that radioactive ray include radioactivity
Position element produce α, β, gamma-rays and all kinds of roentgenotherapia machines or accelerator produce X-ray, electric wire, proton beam and other
Particle beams etc..According to statistics, about 70% cancer patient needs to use radiotherapy during treating cancer, there are about 40%
Cancer can be effected a radical cure with radiotherapy.Effect and status of the radiotherapy in oncotherapy become increasingly conspicuous, it has also become treatment is pernicious swollen
One of Main Means of knurl.
Malignant tumour can be shifted, i.e., the cancer cell in primary malignant neoplasm by blood vessel, lymphatic vessel and tumour around
Tissue, with the operation of blood, lymph and body fluid, to the tissue and organ metastasis of other distant sites, and " taking root ",
" germination ", forms the malignant tumour with primary tumor same property type, because these malignant tumours show as sending out in many places
It is raw, therefore referred to as multiple tumor.
For the radiation cure of multiple tumor, the mode of early stage is to regard multiple tumor as multiple independent to swell
Knurl, carries out radiation cure just for one of tumour every time, and this mode needs repeatedly treatment to complete a course for the treatment of,
Treatment time is long, and treatment cost is high.
The problem that for the above method, occur in that a kind of multiple tumor of similar printer printed document is put again
Ray scanning method, in this approach, regarding multiple tumor as one only needs the huge tumour of local treatment, and this is huge swollen
Region shared by knurl is referred to as the big region of tumour, it is necessary to which the region for the treatment of is actual tumor region in the big region of tumour, without
The region to be treated is actual non-tumor region, radiation generator inswept tumour in the way of printing of inkjet printer document
Big region, radioactive ray are projected in actual tumor region, and radioactive ray are not projected in actual non-tumor region.Although this mode technology
It is relative complex, but seance can just complete a course for the treatment of, substantially reduce treatment time, reduce treatment cost,
Main method as multiple tumor radiation cure at this stage.
In the above-mentioned methods, because radiation generator also wants the non-tumor region of inswept reality, and actual non-tumor area
The area in domain is often far longer than actual tumor region, therefore, and a large amount for the treatment of times have been wasted in actual non-tumor region scanning
During, if it is possible to the sweep time of this subregion is reduced, another reality is rapidly moved to from an actual tumor region
Border tumor region, can substantially reduce treatment time, mitigate Case treatment pain, however, not finding the side of correlation also
Method occurs.
The content of the invention
In view of the above-mentioned problems, the invention discloses a kind of sigmatron region road towards multiple tumor radiotherapy
Footpath optimization method, this method is developed from the multiple tumor radiological scans method of similar printer printed document, is utilized
The characteristics of actual non-tumor region is often much larger than actual tumor region, a tumour point is degenerated to by actual tumor region, will
How radiological scans problem travels through all tumour points and shortest path problem if being converted to, and propose a kind of path optimization side
Method, this method is conducive to substantially reducing treatment time, mitigates Case treatment pain, by artificial intelligence in Medical Devices
Positive facilitation is played in development.
The object of the present invention is achieved like this：
Towards the sigmatron zone routing optimization method of multiple tumor radiotherapy, comprise the following steps：
Step a, actual tumor region is degenerated to actual tumour point, it is determined that the coordinate of actual tumour point；
Specially：
Actual tumour point coordinates is filled up in actual tumour dot matrix, every a line of the actual tumour dot matrix is represented
One actual tumour point coordinates, the first row of actual tumour dot matrix represents actual tumour point abscissa, actual tumour dot matrix
Secondary series represent actual tumour point ordinate；
The distance between step b, calculating actual tumour point of any two, set up distance matrix；
Specially：
Build a ranks number with actual tumour count identical square matrix, the square matrix the i-th row jth row
Represent the distance of i-th of actual j-th of actual tumour point of tumour point distance；
Parameter is explored in step c, initialization, calculates heuristic function initial value；
Specially：
Initialization explores dimension, heuristic factor, retention factors, knowledge matrix, exploration initial value and explores final value；
Heuristic function is the inverse of distance matrix；
Step d, exploration optimal loop path；
Specially：
Since being explored initial value, it is iterated to final value is explored, in iterative process each time, multiple dimension joint explorations
Optimal path, comprises the following steps：
Step d1, under each dimension, using any one actual tumour point as explore starting point, and initialization path record
Table；
Step d2, each dimension of supplement exploration path；
Specially：
Step d21, differentiation have accessed actual tumour point；
Step d22, differentiation actual tumour point to be visited；
Exploration probability between step d23, calculating actual tumour point to be visited；Specially：
Wherein, PijRepresent that actual tumour o'clock has been detected from i-th under the exploration current dimension of probability does not detect reality to j-th
The probability of tumour point, τijFor the i-th row jth column element in knowledge matrix, represent to have detected reality from i-th under the current dimension of guide
Tumour o'clock is to the degree for not detecting actual tumour point for j-th；ηijIt is actual with i-th of actual tumour point and j-th for heuristic function
The distance between tumour point is inversely proportional；β represents heuristic factor；
Step d24, using wheel disc bet method determine the next actual tumour point to be explored；
Step d3, the distance for calculating exploration path under each dimension；
Step d4, the most short exploration distance of calculating；
Step d5, fresh information matrix；Specially：
Above formula is the τ on the right of assignment statement, equationijThe i-th row jth column element in knowledge matrix is represented under current exploration value,
The τ on the equation left sideijThe i-th row jth column element in knowledge matrix is represented under next exploration value, ρ represents retention factors；
Wherein, LengthDimensionRepresent under current dimension, detected total distance of actual tumour point；
Step e, two actual tumour points for finding distance maximum in optimal loop path, optimal loop path is removed described
The line of two actual tumour points, remainder is final path.
The above-mentioned sigmatron zone routing optimization method towards multiple tumor radiotherapy is used to treat multiple swollen
Knurl.
The above-mentioned sigmatron zone routing optimization method towards multiple tumor radiotherapy is in radiotherapy equipment
Application.
Beneficial effect：
Firstth, the present invention is developed from the multiple tumor radiological scans method of similar printer printed document, profit
The characteristics of being often much larger than actual tumor region with actual non-tumor region, a tumour point is degenerated to by actual tumor region,
Radiological scans problem is converted to and how to travel through all tumour points and shortest path problem, and proposes a kind of path optimization side
Method, this method is prevented effectively from a large amount for the treatment of times and has been wasted in actual non-tumor region scanning process, is conducive to dropping significantly
Low treatment time, mitigate Case treatment pain, positive facilitation will be played to development of the artificial intelligence in Medical Devices.
Secondth, in method for optimizing route of the present invention, it is proposed that a kind of alternative manner, by explore dimension, heuristic factor,
Mutual computing between retention factors, knowledge matrix, realizes the exploration to beeline.
3rd, in the methods of the invention, by quoting wheel disc bet method, the change for exploring path is realized, spy is prevented effectively from
Rope path focuses on local optimum.
Brief description of the drawings
Fig. 1 is sigmatron zone routing optimization method flow chart of the present invention towards multiple tumor radiotherapy.
Fig. 2 is the operation result of the program of emulation experiment.
Fig. 3 is the Matlab software interface sectional drawings of emulation experiment.
Embodiment
The specific embodiment of the invention is described in further detail below in conjunction with the accompanying drawings.
Embodiment one
The following is the present invention towards the sigmatron zone routing optimization method of multiple tumor radiotherapy embodiment party
Formula.
The sigmatron zone routing optimization method towards multiple tumor radiotherapy of present embodiment, flow chart
As shown in figure 1, this method comprises the following steps：
Step a, actual tumor region is degenerated to actual tumour point, it is determined that the coordinate of actual tumour point；
Specially：
Actual tumour point coordinates is filled up in actual tumour dot matrix, every a line of the actual tumour dot matrix is represented
One actual tumour point coordinates, the first row of actual tumour dot matrix represents actual tumour point abscissa, actual tumour dot matrix
Secondary series represent actual tumour point ordinate；
The distance between step b, calculating actual tumour point of any two, set up distance matrix；
Specially：
Build a ranks number with actual tumour count identical square matrix, the square matrix the i-th row jth row
Represent the distance of i-th of actual j-th of actual tumour point of tumour point distance；
Parameter is explored in step c, initialization, calculates heuristic function initial value；
Specially：
Initialization explores dimension, heuristic factor, retention factors, knowledge matrix, exploration initial value and explores final value；
Heuristic function is the inverse of distance matrix；
Step d, exploration optimal loop path；
Specially：
Since being explored initial value, it is iterated to final value is explored, in iterative process each time, multiple dimension joint explorations
Optimal path, comprises the following steps：
Step d1, under each dimension, using any one actual tumour point as explore starting point, and initialization path record
Table；
Step d2, each dimension of supplement exploration path；
Specially：
Step d21, differentiation have accessed actual tumour point；
Step d22, differentiation actual tumour point to be visited；
Exploration probability between step d23, calculating actual tumour point to be visited；Specially：
Wherein, PijRepresent that actual tumour o'clock has been detected from i-th under the exploration current dimension of probability does not detect reality to j-th
The probability of tumour point, τijFor the i-th row jth column element in knowledge matrix, represent to have detected reality from i-th under the current dimension of guide
Tumour o'clock is to the degree for not detecting actual tumour point for j-th；ηijIt is actual with i-th of actual tumour point and j-th for heuristic function
The distance between tumour point is inversely proportional；β represents heuristic factor；
Step d24, using wheel disc bet method determine the next actual tumour point to be explored；
Step d3, the distance for calculating exploration path under each dimension；
Step d4, the most short exploration distance of calculating；
Step d5, fresh information matrix；Specially：
Above formula is the τ on the right of assignment statement, equationijThe i-th row jth column element in knowledge matrix is represented under current exploration value,
The τ on the equation left sideijThe i-th row jth column element in knowledge matrix is represented under next exploration value, ρ represents retention factors；
Wherein, LengthDimensionRepresent under current dimension, detected total distance of actual tumour point；
Step e, two actual tumour points for finding distance maximum in optimal loop path, optimal loop path is removed described
The line of two actual tumour points, remainder is final path.
Below with Matlab to the present invention towards multiple tumor radiotherapy sigmatron zone routing optimization method
Emulated, simulated program is as follows：
The operation result of the program of emulation experiment is as shown in Fig. 2 figure it is seen that beeline is 2487.9366
Unit.
The Matlab software interfaces sectional drawing of emulation experiment as shown in figure 3, from figure 3, it can be seen that most short path 6,9,1,
8th, 2,10,5,7,4,3, software used time 1.248304s.
Embodiment two
Application the following is the present invention towards the sigmatron zone routing optimization method of multiple tumor radiotherapy is real
Apply example.
The sigmatron zone routing optimization method towards multiple tumor radiotherapy in present embodiment, for tool
Method described in body embodiment one, methods described is used to treat multiple tumor.
Embodiment three
Application the following is the present invention towards the sigmatron zone routing optimization method of multiple tumor radiotherapy is real
Apply example.
The sigmatron zone routing optimization method towards multiple tumor radiotherapy in present embodiment, for tool
Method described in body embodiment one, methods described is applied to radiotherapy equipment.
Claims (3)
1. towards the sigmatron zone routing optimization method of multiple tumor radiotherapy, it is characterised in that including following step
Suddenly：
Step a, actual tumor region is degenerated to actual tumour point, it is determined that the coordinate of actual tumour point；
Specially：
Actual tumour point coordinates is filled up in actual tumour dot matrix, every a line of the actual tumour dot matrix represents one
Actual tumour point coordinates, the first row of actual tumour dot matrix represents actual tumour point abscissa, the of actual tumour dot matrix
Two row represent actual tumour point ordinate；
The distance between step b, calculating actual tumour point of any two, set up distance matrix；
Specially：
Build a ranks number with actual tumour count identical square matrix, the square matrix the i-th row jth row represent
The distance of i-th of actual j-th of actual tumour point of tumour point distance；
Parameter is explored in step c, initialization, calculates heuristic function initial value；
Specially：
Initialization explores dimension, heuristic factor, retention factors, knowledge matrix, exploration initial value and explores final value；
Heuristic function is the inverse of distance matrix；
Step d, exploration optimal loop path；
Specially：
Since being explored initial value, it is iterated to final value is explored, in iterative process each time, multiple dimension joint explorations are optimal
Path, comprises the following steps：
Step d1, under each dimension, using any one actual tumour point as exploring starting point, and initialization path record sheet；
Step d2, each dimension of supplement exploration path；
Specially：
Step d21, differentiation have accessed actual tumour point；
Step d22, differentiation actual tumour point to be visited；
Exploration probability between step d23, calculating actual tumour point to be visited；Specially：
Wherein, PijRepresent that actual tumour o'clock has been detected from i-th under the exploration current dimension of probability does not detect actual tumour to j-th
The probability of point, τijFor the i-th row jth column element in knowledge matrix, represent to have detected actual tumour from i-th under the current dimension of guide
O'clock to the degree for not detecting actual tumour point for j-th；ηijFor heuristic function, with i-th of actual tumour point and j-th of actual tumour
The distance between point is inversely proportional；β represents heuristic factor；
Step d24, using wheel disc bet method determine the next actual tumour point to be explored；
Step d3, the distance for calculating exploration path under each dimension；
Step d4, the most short exploration distance of calculating；
Step d5, fresh information matrix；Specially：
Above formula is the τ on the right of assignment statement, equationijRepresent under current exploration value the i-th row jth column element, equation in knowledge matrix
The τ on the left sideijThe i-th row jth column element in knowledge matrix is represented under next exploration value, ρ represents retention factors；
Wherein, LengthDimensionRepresent under current dimension, detected total distance of actual tumour point；
Step e, two actual tumour points for finding distance maximum in optimal loop path, optimal loop path removes described two
The line of actual tumour point, remainder is final path.
2. the sigmatron zone routing optimization method described in claim 1 towards multiple tumor radiotherapy is used to treat
Multiple tumor.
3. the sigmatron zone routing optimization method described in claim 1 and 2 towards multiple tumor radiotherapy is in radiation
Application in therapeutic equipment.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102752721A (en) * | 2012-06-28 | 2012-10-24 | 上海交通大学 | Route recovery method suitable for interference environment of wireless sensor network |
| CN102743821A (en) * | 2011-04-18 | 2012-10-24 | 株式会社日立制作所 | Treatment planning apparatus and particle therapy apparatus |
| CN104284696A (en) * | 2012-05-14 | 2015-01-14 | 三菱电机株式会社 | Particle beam scanning irradiation system |
| CN105654202A (en) * | 2015-12-30 | 2016-06-08 | 中国科学院合肥物质科学研究院 | Method for optimizing proton radiotherapy path in active scanning manner by considering scanning speed change |
| US20170036037A1 (en) * | 2014-04-30 | 2017-02-09 | Stc.Unm | Optimization methods for radiation therapy planning |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102743821A (en) * | 2011-04-18 | 2012-10-24 | 株式会社日立制作所 | Treatment planning apparatus and particle therapy apparatus |
| CN104284696A (en) * | 2012-05-14 | 2015-01-14 | 三菱电机株式会社 | Particle beam scanning irradiation system |
| CN102752721A (en) * | 2012-06-28 | 2012-10-24 | 上海交通大学 | Route recovery method suitable for interference environment of wireless sensor network |
| US20170036037A1 (en) * | 2014-04-30 | 2017-02-09 | Stc.Unm | Optimization methods for radiation therapy planning |
| CN105654202A (en) * | 2015-12-30 | 2016-06-08 | 中国科学院合肥物质科学研究院 | Method for optimizing proton radiotherapy path in active scanning manner by considering scanning speed change |
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