CN109741830B - Single-cycle and double-cycle mixed judgment type chest and abdomen surface area respiratory signal cycle prediction method - Google Patents
Single-cycle and double-cycle mixed judgment type chest and abdomen surface area respiratory signal cycle prediction method Download PDFInfo
- Publication number
- CN109741830B CN109741830B CN201910018166.9A CN201910018166A CN109741830B CN 109741830 B CN109741830 B CN 109741830B CN 201910018166 A CN201910018166 A CN 201910018166A CN 109741830 B CN109741830 B CN 109741830B
- Authority
- CN
- China
- Prior art keywords
- signal
- period
- cycle
- simulated
- pause
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention relates to a single-period and double-period mixed judgment chest and abdomen surface area respiration signal period prediction method, belonging to the technical fields of oncology, precise instruments, engineering technology, mathematics and the like; the method comprises the steps of firstly constructing an ideal single-cycle respiration signal, then carrying out cycle continuation to obtain an ideal multi-cycle respiration signal, and finally carrying out cycle extraction on the ideal multi-cycle respiration signal, wherein the whole extraction process is carried out in two imaginary cycles with twice data quantity, and the cycle extraction can be completed in the two cycles; the method can accurately extract the period of the ideal multi-period respiratory signal and lay the foundation of a simulation experiment for accurately predicting respiratory motion.
Description
Technical Field
The invention discloses a single-period and double-period mixed judgment method for predicting the period of a respiratory signal of a chest and abdomen surface area, and belongs to the technical fields of oncology, precise instruments, engineering technology, mathematics and the like.
Background
Radiation therapy (hereinafter, simply referred to as radiotherapy) is one of the most important means for treating cancer. About 70% of cancer patients are treated with radiation therapy, and about 40% of cancers can be cured by radiation therapy. The effectiveness of radiation therapy is related to the accuracy and dose of radiation exposure to the tumor area. Malignant tumors of the digestive system are positioned in the thoracic cavity and the abdominal cavity and are influenced by respiratory motion, and the positions and the volumes of the tumors can be changed along with time, so that the radiation irradiation precision is reduced, and the radiotherapy effect is influenced.
In order to solve the problem that the radiotherapy effect is reduced by respiratory motion, many scholars develop the research work of technologies or methods such as target area expansion, breath holding, respiratory gating, passive pressurization, four-dimensional radiotherapy, real-time tracking and the like. However, because these works are all lag compensation works which are carried out after the respiratory movement occurs, the problem that the respiratory movement reduces the radiotherapy effect cannot be fundamentally overcome.
To solve the above problem, some scholars began to study lead compensation methods, which first require prediction of respiratory motion. Currently, respiratory motion prediction methods can be divided into the following two broad categories: the first model prediction method is that a breathing motion model is established by monitoring early-stage breathing motion data, and then future breathing motion is presumed based on the model; and the second model-free prediction method is trained by observed respiratory motion patterns to form a heuristic learning algorithm, and the future respiratory motion is predicted by learning.
Although the breathing movement repeats the inspiration and expiration actions continuously, the breathing movement is not simply repeated by taking inspiration and expiration as a period, the period and the amplitude change under the influence of the breathing movement and the outside in each inspiration and expiration process, and the model prediction method cannot take care of the change, so that the prediction accuracy is limited, and more scholars begin to try in a model-free prediction method, for example, the prediction of the breathing movement by using the Gaussian process regression.
Gaussian process regression is a universal prediction algorithm that predicts future data by learning known data, and the prediction results are given in the form of mean and variance. Since the gaussian process regression algorithm itself is not proposed purely for respiratory motion prediction, some constraints of respiratory motion are not considered. If the constraint condition of the respiratory motion is taken into consideration, the prediction range is narrowed, and the prediction result is more accurate.
For respiratory motion, the frequency is limited within a certain range, so that the prediction result can be constrained by acquiring the period or frequency of the respiratory signal, and the prediction precision is improved. Therefore, the period of the respiratory motion is acquired, so that the prediction precision is improved.
However, since the respiratory motion is not a simple repetition of a single cycle, it is difficult to determine the cycle by the distance of two identical feature values. Then, if the period of the respiratory motion is acquired, it becomes a key technical problem to improve the prediction accuracy.
Disclosure of Invention
In order to predict the period of the respiratory signal, the invention starts from an ideal respiratory signal and provides a respiratory signal period extraction method, which not only comprises the work of constructing the ideal respiratory signal according to the respiratory rule, but also comprises the work of extracting the ideal respiratory signal period.
The purpose of the invention is realized as follows:
the single-cycle and double-cycle mixed judgment chest and abdomen surface area respiratory signal cycle prediction method comprises the following steps:
step a, constructing an ideal single-cycle respiratory signal;
b, carrying out periodic continuation on the ideal single-period respiratory signal obtained in the step a to obtain an ideal multi-period respiratory signal;
step c, carrying out periodic extraction on the ideal multi-periodic respiratory signal obtained in the step b, wherein the periodic extraction comprises the following steps:
step c1, extracting the direct current component of the ideal multicycle respiratory signal obtained in the step b;
c2, subtracting the direct-current component obtained in the step c1 from the ideal multi-period respiratory signal obtained in the step b;
step c3, setting a threshold value;
step c4, setting a period data variable as 1, and entering step c5;
step c5, calculating the sum of all data in the first period and the sum of all data in the first and second periods according to the period data variable, and entering the step c3;
step c6, judging whether the difference between the sum of all the data in the first period and the sum of all the data in the first second period is larger than a threshold value, if so:
if yes, the periodic data variable is +1, and the step c5 is returned;
if not, entering the step c7;
and c7, the period data variable is the period of the multicycle respiratory signal.
The method for predicting the period of the respiratory signal of the chest and abdomen surface area by single-period and double-period mixed judgment comprises the following steps of:
a1, according to the normal breathing process of a human, dividing the breathing motion into three stages of an inspiration process, an expiration process and a pause-like process;
step a2, respectively determining the duration T of the inspiration process 1 Duration of the exhalation process T 2 And duration T of pause-like procedure 3 ；
Step a3, the using period is 4T 1 The phase is [0, pi/2]The sine function simulates the inspiration process to obtain a simulated inspiration signal; with a period of 4T 2 The phase is [ pi/2, pi ]]The sine function simulates the exhalation process to obtain a simulated exhalation signal; with a period of 4T 3 The phase is [ pi, 3 pi/2]Simulating a class pause process by the sine function to obtain a simulated class pause signal;
step a4, adjusting the relative amplitude of the analog inspiration signal to be between [ a and b ], adjusting the relative amplitude of the analog expiration signal to be between [ c and b ], and adjusting the relative amplitude of the analog pause signal to be between [ a and c ];
and a5, connecting the obtained simulated inspiration signal, the simulated expiration signal and the simulated pause signal end to obtain an ideal single-cycle respiration signal.
The single-cycle and double-cycle mixed judgment chest and abdomen surface area respiratory signal cycle prediction method comprises the following steps:
step a, constructing an ideal single-cycle respiratory signal;
a1, according to the normal breathing process of human, dividing the breathing movement into three stages of an inspiration process, an expiration process and a pause-like process;
step a2, respectively determining the duration T of the inspiration process 1 Duration of the exhalation process T 2 And duration T of pause-like procedure 3 ；
Step a3, the using period is 4T 1 The phase is [0, π/2]]The sine function simulates the inspiration process to obtain a simulated inspiration signal; with a period of 4T 2 The phase is [ pi/2, pi]The sine function simulates the exhalation process to obtain a simulated exhalation signal; with a period of 4T 3 The phase is [ pi, 3 pi/2]Simulating a class pause process by the sine function to obtain a simulated class pause signal;
step a4, adjusting the relative amplitude of the analog inspiration signal to be between [ a and b ], adjusting the relative amplitude of the analog expiration signal to be between [ c and b ], and adjusting the relative amplitude of the analog pause signal to be between [ a and c ];
step a5, connecting the obtained simulated inspiration signal, simulated expiration signal and simulated pause signal end to obtain an ideal single-cycle respiration signal;
b, carrying out periodic continuation on the ideal single-period respiratory signal obtained in the step a to obtain an ideal multi-period respiratory signal;
step c, carrying out periodic extraction on the ideal multi-periodic respiratory signal obtained in the step b, wherein the periodic extraction comprises the following steps:
step c1, extracting the direct current component of the ideal multicycle respiratory signal obtained in the step b;
c2, subtracting the direct-current component obtained in the step c1 from the ideal multi-period respiratory signal obtained in the step b;
step c3, setting a threshold value;
step c4, setting a period data variable as 1, and entering step c5;
step c5, calculating the sum of all data in the first period and the sum of all data in the first and second periods according to the period data variable, and entering the step c3;
step c6, judging whether the difference between the sum of all the data in the first period and the sum of all the data in the first second period is larger than a threshold value, if so:
if yes, the periodic data variable is +1, and the step c5 is returned;
if not, entering the step c7;
and c7, the period data variable is the period of the multicycle respiratory signal.
A method for constructing an ideal monocycle respiratory signal comprises the following steps:
a1, according to the normal breathing process of a human, dividing the breathing motion into three stages of an inspiration process, an expiration process and a pause-like process;
step a2, respectively determining the duration T of the inspiration process 1 Duration of the exhalation process T 2 And duration T of pause-like procedure 3 ；
Step a3, the using period is 4T 1 The phase is [0, π/2]]The sine function simulates the inspiration process to obtain a simulated inspiration signal; with a period of 4T 2 The phase is [ pi/2, pi ]]The sine function simulates the exhalation process to obtain a simulated exhalation signal; with a period of 4T 3 The phase is [ pi, 3 pi/2]Simulating a class pause process by the sine function to obtain a simulated class pause signal;
step a4, adjusting the relative amplitude of the analog inspiration signal to be between [ a and b ], adjusting the relative amplitude of the analog expiration signal to be between [ c and b ], and adjusting the relative amplitude of the analog pause signal to be between [ a and c ];
and a5, connecting the obtained simulated inspiration signal, the simulated expiration signal and the simulated pause signal end to obtain an ideal single-cycle respiration signal.
A method for extracting ideal multicycle respiratory signal cycle comprises the following steps:
step c1, extracting the direct current component of the ideal multicycle respiratory signal obtained in the step b;
c2, subtracting the direct current component obtained in the step c1 from the ideal multi-period respiratory signal obtained in the step b;
step c3, setting a threshold value;
step c4, setting a period data variable as 1, and entering step c5;
step c5, calculating the sum of all data in the first period and the sum of all data in the first and second periods according to the period data variables, and entering step c3;
step c6, judging whether the difference between the sum of all the data in the first period and the sum of all the data in the first second period is larger than a threshold value, if so:
if yes, the periodic data variable is +1, and the step c5 is returned;
if not, entering the step c7;
and c7, the period data variable is the period of the multicycle respiratory signal.
Has the advantages that:
first, although the present invention belongs to the technical field of oncology, the present invention is to extract a signal feature quantity from a technical point of view, and is not a method for diagnosing and treating a disease described in the twenty-fifth paragraph of patent law because it cannot diagnose and treat a disease from the technical purpose and effect of the present invention alone.
Secondly, the present disclosure is sufficient enough that the execution result can be obtained by only executing the source code described in the specification part in MATLAB software, and the present application can be implemented by those skilled in the art or those not skilled in the art.
The invention further provides an ideal single-cycle respiratory signal construction method, the respiratory signal in one cycle can be fitted by only using three sections of sine functions, the method is simple, the functions are simple, and the fitting result corresponds to the real respiratory motion.
Fourthly, the method is carried out in two hypothetical weeks with the same data volume, and compared with the invention patent 'method for predicting the period of the respiratory signal of the chest and abdomen surface area of the human body based on variance calculation' which is filed on the same day by the research team, the period extraction can be completed in a real period, so the calculated amount is smaller, and the operation time can be improved from 0.40s to 0.26s from the simulation result.
Fifthly, the method is carried out in two hypothetical weeks with the same data volume, and the invention patent 'the prediction method of the respiration signal period of the chest and abdomen surface area by combining three-period judgment', which is filed on the same day by the research team, considers that the expiration and inspiration processes of the respiration motion are asymmetric, so that the mutual verification of data can be realized in the two hypothetical periods, the occurrence of the hypothetical periods is avoided, the prediction result is more accurate, the running time can be further improved, and the running time can be improved from 0.32s to 0.26s from the simulation result.
Drawings
Fig. 1 is a graph of an ideal multicycle respiratory signal.
Fig. 2 is a program operation result at the time of cycle extraction.
Fig. 3 is a program execution interface.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The following describes in further detail specific embodiments of the present invention with reference to the accompanying drawings.
Detailed description of the preferred embodiment
The embodiment is a single-cycle and double-cycle mixed judgment chest and abdomen surface area respiratory signal cycle prediction method embodiment.
The method for predicting the period of the respiratory signal of the chest and abdomen surface area by single-period and double-period mixed judgment in the embodiment comprises the following steps:
step a, constructing an ideal single-cycle respiratory signal;
b, carrying out periodic continuation on the ideal single-period respiratory signal obtained in the step a to obtain an ideal multi-period respiratory signal;
step c, carrying out periodic extraction on the ideal multi-periodic respiratory signal obtained in the step b, wherein the periodic extraction comprises the following steps:
step c1, extracting the direct current component of the ideal multicycle respiratory signal obtained in the step b;
c2, subtracting the direct current component obtained in the step c1 from the ideal multi-period respiratory signal obtained in the step b;
step c3, setting a threshold value;
step c4, setting a period data variable as 1, and entering step c5;
step c5, calculating the sum of all data in the first period and the sum of all data in the first and second periods according to the period data variable, and entering the step c3;
step c6, judging whether the difference between the sum of all the data in the first period and the sum of all the data in the first and second periods is larger than a threshold value, if so:
if yes, the periodic data variable is +1, and the step c5 is returned;
if not, entering the step c7;
and c7, the period data variable is the period of the multicycle respiratory signal.
Detailed description of the invention
The embodiment is an embodiment of a method for predicting the period of a respiratory signal of a chest and abdomen surface area by single-period and double-period mixed judgment.
The method for predicting the period of the respiratory signal of the thoracoabdominal surface region based on single-period and double-period mixed judgment in the embodiment further defines the step a of constructing the ideal single-period respiratory signal on the basis of the specific embodiment one, and comprises the following steps:
a1, according to the normal breathing process of human, dividing the breathing movement into three stages of an inspiration process, an expiration process and a pause-like process;
step a2, respectively determining the duration T of the inspiration process 1 Duration of the exhalation procedure T 2 And duration T of pause-like procedure 3 ；
Step a3, the using period is 4T 1 The phase is [0, pi/2]The sine function simulates the inspiration process to obtain a simulated inspiration signal; with a period of 4T 2 The phase is [ pi/2, pi]The sine function simulates the exhalation process to obtain a simulated exhalation signal; with a period of 4T 3 The phase is [ pi, 3 pi/2]Is turning toA chord function simulation pause process is carried out to obtain a simulation pause signal;
step a4, adjusting the relative amplitude of the analog inspiration signal to be between [ a and b ], adjusting the relative amplitude of the analog expiration signal to be between [ c and b ], and adjusting the relative amplitude of the analog pause signal to be between [ a and c ];
and a5, connecting the obtained simulated inspiration signal, the simulated expiration signal and the simulated pause signal end to obtain an ideal single-cycle respiration signal.
Detailed description of the preferred embodiment
The embodiment is a single-cycle and double-cycle mixed judgment chest and abdomen surface area respiratory signal cycle prediction method embodiment.
The method for predicting the period of the respiratory signal of the chest-abdomen surface area by single-period and double-period mixed judgment comprises the following steps of:
step a, constructing an ideal single-cycle respiratory signal;
a1, according to the normal breathing process of a human, dividing the breathing motion into three stages of an inspiration process, an expiration process and a pause-like process;
step a2, respectively determining the duration T of the inspiration process 1 Duration of the exhalation process T 2 And duration T of pause-like process 3 ；
Step a3, the using period is 4T 1 The phase is [0, pi/2]The sine function simulates the inspiration process to obtain a simulated inspiration signal; with a period of 4T 2 The phase is [ pi/2, pi]The sine function simulates the exhalation process to obtain a simulated exhalation signal; with a period of 4T 3 The phase is [ pi, 3 pi/2]Simulating a class pause process by the sine function to obtain a simulated class pause signal;
step a4, adjusting the relative amplitude of the analog inspiration signal to be between [ a and b ], adjusting the relative amplitude of the analog expiration signal to be between [ c and b ], and adjusting the relative amplitude of the analog pause signal to be between [ a and c ];
step a5, connecting the obtained simulated inspiration signal, simulated expiration signal and simulated pause signal end to obtain an ideal single-cycle respiration signal;
b, carrying out period continuation on the ideal single-period respiratory signal obtained in the step a to obtain an ideal multi-period respiratory signal;
step c, carrying out periodic extraction on the ideal multi-periodic respiratory signal obtained in the step b, wherein the periodic extraction comprises the following steps:
step c1, extracting the direct current component of the ideal multicycle respiratory signal obtained in the step b;
c2, subtracting the direct current component obtained in the step c1 from the ideal multi-period respiratory signal obtained in the step b;
step c3, setting a threshold value;
step c4, setting a period data variable as 1, and entering step c5;
step c5, calculating the sum of all data in the first period and the sum of all data in the first and second periods according to the period data variable, and entering the step c3;
step c6, judging whether the difference between the sum of all the data in the first period and the sum of all the data in the first and second periods is larger than a threshold value, if so:
if yes, the periodic data variable is +1, and the step c5 is returned;
if not, entering the step c7;
and c7, the period data variable is the period of the multicycle respiratory signal.
Detailed description of the invention
The embodiment is an embodiment of an ideal single-cycle respiratory signal construction method.
The method for constructing the ideal single-cycle respiratory signal comprises the following steps:
a1, according to the normal breathing process of human, dividing the breathing movement into three stages of an inspiration process, an expiration process and a pause-like process;
step a2, respectively determining the duration T of the inspiration process 1 Duration of the exhalation procedure T 2 And duration T of pause-like process 3 ；
Step a3, the using period is 4T 1 The phase is [0, pi/2]The sine function of the simulation model simulates an inspiration process to obtain a simulation inspiration signal; with a period of 4T 2 The phase is [ pi/2, pi]The sine function simulates the exhalation process to obtain a simulated exhalation signal; with a period of 4T 3 The phase is [ pi, 3 pi/2]Simulating a class pause process by the sine function to obtain a simulated class pause signal;
step a4, adjusting the relative amplitude of the analog inspiration signal to be between [ a and b ], adjusting the relative amplitude of the analog expiration signal to be between [ c and b ], and adjusting the relative amplitude of the analog pause signal to be between [ a and c ];
and a5, connecting the obtained simulated inspiration signal, the simulated expiration signal and the simulated pause signal end to obtain an ideal single-cycle respiration signal.
Detailed description of the preferred embodiment
The embodiment is an embodiment of an ideal multi-cycle respiratory signal cycle extraction method.
The method for extracting the ideal multicycle respiratory signal cycle of the embodiment comprises the following steps:
step c1, extracting the direct current component of the ideal multicycle respiratory signal obtained in the step b;
c2, subtracting the direct-current component obtained in the step c1 from the ideal multi-period respiratory signal obtained in the step b;
step c3, setting a threshold value;
step c4, setting a period data variable as 1, and entering step c5;
step c5, calculating the sum of all data in the first period and the sum of all data in the first and second periods according to the period data variable, and entering the step c3;
step c6, judging whether the difference between the sum of all the data in the first period and the sum of all the data in the first and second periods is larger than a threshold value, if so:
if yes, the periodic data variable is +1, and the step c5 is returned;
if not, entering the step c7;
and c7, the period data variable is the period of the multicycle respiratory signal.
Detailed description of the preferred embodiment
The embodiment is an embodiment of a method for predicting the period of a respiratory signal of a chest and abdomen surface area by single-period and double-period mixed judgment.
To validate the inventive method, the method was run on MATLAB R2014a software. The computer configuration applied is as follows:
computer configuration table
| Operating system | Windows 7 flagship edition X86 |
| Processor with a memory for storing a plurality of data | Intel(R)Core(TM)i5-8250OU@1.60GHz 1.80GHz |
| Installing an internal memory | 8.00GB |
The MATLAB program was written as follows:
the program operation results are shown in fig. 1, fig. 2 and fig. 3, respectively. Fig. 1 is a signal diagram of an ideal multicycle respiratory signal, fig. 2 is a program operation result in cycle extraction, and fig. 3 is a program operation interface.
The program operation result shows that the method accurately extracts the signal period from the respiratory motion signal.
Claims (2)
1. The single-cycle and double-cycle mixed judgment chest and abdomen surface area respiratory signal cycle prediction method is characterized by comprising the following steps of:
step a, constructing an ideal single-cycle respiratory signal, comprising the following steps:
a1, according to the normal breathing process of human, dividing the breathing movement into three stages of an inspiration process, an expiration process and a pause-like process;
step a2, respectively determining the duration T1 of an inspiration process, the duration T2 of an expiration process and the duration T3 of a pause-like process;
a3, simulating an air suction process by using a sine function with a period of 4T1 and a phase of [0, pi/2 ] to obtain a simulated air suction signal; simulating the expiration process by using a sine function with the period of 4T2 and the phase of [ pi/2, pi ] to obtain a simulated expiration signal; simulating a class pause process by using a sine function with a period of 4T3 and a phase of [ pi, 3 pi/2 ] to obtain a simulated class pause signal;
step a4, adjusting the relative amplitude of the analog inspiration signal to be between [ a and b ], adjusting the relative amplitude of the analog expiration signal to be between [ c and b ], and adjusting the relative amplitude of the analog pause signal to be between [ a and c ];
step a5, connecting the obtained simulated inspiration signal, simulated expiration signal and simulated pause signal end to obtain an ideal single-cycle respiration signal;
b, carrying out periodic continuation on the ideal single-period respiratory signal obtained in the step a to obtain an ideal multi-period respiratory signal;
step c, carrying out periodic extraction on the ideal multicycle respiratory signal obtained in the step b, and comprising the following steps of:
c1, extracting the direct current component of the ideal multicycle respiratory signal obtained in the step b;
c2, subtracting the direct current component obtained in the step c1 from the ideal multi-period respiratory signal obtained in the step b;
step c3, setting a threshold value;
step c4, setting a period data variable as 1, and entering step c5;
step c5, calculating the sum of all data in the first period and the sum of all data in the first and second periods according to the period data variable, and entering the step c3;
step c6, judging whether the difference between the sum of all the data in the first period and the sum of all the data in the first second period is larger than a threshold value, if so:
if yes, the periodic data variable is +1, and the step c5 is returned;
if not, entering the step c7;
and c7, the period data variable is the period of the multicycle respiratory signal.
2. A method for constructing an ideal monocycle respiratory signal is characterized by comprising the following steps:
a1, according to the normal breathing process of human, dividing the breathing movement into three stages of an inspiration process, an expiration process and a pause-like process;
step a2, respectively determining the duration T1 of an inspiration process, the duration T2 of an expiration process and the duration T3 of a pause-like process;
a3, simulating an air suction process by using a sine function with a period of 4T1 and a phase of [0, pi/2 ] to obtain a simulated air suction signal; simulating the expiration process by using a sine function with the period of 4T2 and the phase of [ pi/2, pi ] to obtain a simulated expiration signal; simulating a class pause process by using a sine function with a period of 4T3 and a phase of [ pi, 3 pi/2 ] to obtain a simulated class pause signal;
step a4, adjusting the relative amplitude of the analog inspiration signal to be between [ a and b ], adjusting the relative amplitude of the analog expiration signal to be between [ c and b ], and adjusting the relative amplitude of the analog pause signal to be between [ a and c ];
and a5, connecting the obtained simulated inspiration signal, the simulated expiration signal and the simulated pause signal end to obtain an ideal single-cycle respiration signal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910018166.9A CN109741830B (en) | 2019-01-09 | 2019-01-09 | Single-cycle and double-cycle mixed judgment type chest and abdomen surface area respiratory signal cycle prediction method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910018166.9A CN109741830B (en) | 2019-01-09 | 2019-01-09 | Single-cycle and double-cycle mixed judgment type chest and abdomen surface area respiratory signal cycle prediction method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109741830A CN109741830A (en) | 2019-05-10 |
| CN109741830B true CN109741830B (en) | 2022-12-06 |
Family
ID=66363966
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910018166.9A Active CN109741830B (en) | 2019-01-09 | 2019-01-09 | Single-cycle and double-cycle mixed judgment type chest and abdomen surface area respiratory signal cycle prediction method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109741830B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109741827B (en) * | 2019-01-09 | 2022-11-01 | 哈尔滨理工大学 | Chest and abdomen surface area respiratory signal period prediction method combining double period judgment |
| CN109741829B (en) * | 2019-01-09 | 2022-10-28 | 哈尔滨理工大学 | Chest and abdomen surface area respiratory signal period prediction method combining three-period judgment |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2008686C1 (en) * | 1991-07-09 | 1994-02-28 | Ростовский медицинский институт | Method for forecasting development of complications in children suffering from generalized respiratory conservative infection |
| CN101628154A (en) * | 2008-07-16 | 2010-01-20 | 深圳市海博科技有限公司 | Image guiding and tracking method based on prediction |
| CN101637388A (en) * | 2008-07-29 | 2010-02-03 | 深圳市海博科技有限公司 | Respiratory movement predicting method |
| CN102481127A (en) * | 2009-08-13 | 2012-05-30 | 帝人制药株式会社 | Device for calculating respiratory waveform information and medical device using respiratory waveform information |
| CN102613964A (en) * | 2012-03-12 | 2012-08-01 | 深圳市视聆科技开发有限公司 | Method and system for acquiring physiological signal cycle |
| TW201544074A (en) * | 2014-05-22 | 2015-12-01 | Apex Medical Corp | Breathing waveform recognition method and system thereof |
| CN105286998A (en) * | 2015-11-03 | 2016-02-03 | 苏州大学 | Simulation device for human body pleuroperitoneal cavity movement caused by breathing |
-
2019
- 2019-01-09 CN CN201910018166.9A patent/CN109741830B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2008686C1 (en) * | 1991-07-09 | 1994-02-28 | Ростовский медицинский институт | Method for forecasting development of complications in children suffering from generalized respiratory conservative infection |
| CN101628154A (en) * | 2008-07-16 | 2010-01-20 | 深圳市海博科技有限公司 | Image guiding and tracking method based on prediction |
| CN101637388A (en) * | 2008-07-29 | 2010-02-03 | 深圳市海博科技有限公司 | Respiratory movement predicting method |
| CN102481127A (en) * | 2009-08-13 | 2012-05-30 | 帝人制药株式会社 | Device for calculating respiratory waveform information and medical device using respiratory waveform information |
| CN102613964A (en) * | 2012-03-12 | 2012-08-01 | 深圳市视聆科技开发有限公司 | Method and system for acquiring physiological signal cycle |
| TW201544074A (en) * | 2014-05-22 | 2015-12-01 | Apex Medical Corp | Breathing waveform recognition method and system thereof |
| CN105286998A (en) * | 2015-11-03 | 2016-02-03 | 苏州大学 | Simulation device for human body pleuroperitoneal cavity movement caused by breathing |
Non-Patent Citations (2)
| Title |
|---|
| 基于三维傅里叶变换的胸腹表面测量;孟晓亮;《光学精密工程》;20180430;第26卷(第4期);778-785页 * |
| 基于后验概率的呼吸信号预测;周寿军;《中国医学生物工程学报》;20090430;第28卷(第2期);213-220页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109741830A (en) | 2019-05-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP3695882A1 (en) | Computing radiotherapy dose distribution | |
| JP6619889B2 (en) | Treatment control using motion prediction | |
| CN109741830B (en) | Single-cycle and double-cycle mixed judgment type chest and abdomen surface area respiratory signal cycle prediction method | |
| CN109741828B (en) | Human chest and abdomen surface area respiratory signal period prediction method in radiotherapy | |
| CN109741831B (en) | Human chest and abdomen surface area respiratory signal period prediction method based on variance calculation | |
| Seregni et al. | Real-time tumor tracking with an artificial neural networks-based method: a feasibility study | |
| Li et al. | Artificial intelligence in radiotherapy | |
| CN115485018A (en) | Method and apparatus for controlling process delivery using reinforcement learning | |
| Korreman et al. | The changing role of radiation oncology professionals in a world of AI–Just jobs lost–Or a solution to the under-provision of radiotherapy? | |
| Sterpin et al. | Helical tomotherapy for SIB and hypo-fractionated treatments in lung carcinomas: a 4D Monte Carlo treatment planning study | |
| CN108899093A (en) | Intensity modulated radiation therapy intended dose indication item prediction technique based on intelligence learning | |
| CN109741829B (en) | Chest and abdomen surface area respiratory signal period prediction method combining three-period judgment | |
| CN109741827B (en) | Chest and abdomen surface area respiratory signal period prediction method combining double period judgment | |
| Pastor-Serrano et al. | Learning the physics of particle transport via transformers | |
| Li et al. | A novel deep learning framework for internal gross target volume definition from 4D computed tomography of lung cancer patients | |
| Chen et al. | Application of deep learning to auto-delineation of target volumes and organs at risk in radiotherapy | |
| Modiri et al. | Inversed-planned respiratory phase gating in lung conformal radiation therapy | |
| Rostampour et al. | Markerless respiratory tumor motion prediction using an adaptive neuro-fuzzy approach | |
| Miandoab et al. | Investigation of the optimum location of external markers for patient setup accuracy enhancement at external beam radiotherapy | |
| Teo et al. | Deterministic small‐scale undulations of image‐based risk predictions from the deep learning of lung tumors in motion | |
| Waghorn et al. | A comparison of the dosimetric effects of intrafraction motion on step‐and‐shoot, compensator, and helical tomotherapy‐based IMRT | |
| Shan et al. | A comparative study on the generalization ability of back propagation neural network and support vector machine for tracking tumor motion in radiotherapy | |
| Musselman et al. | System based monitoring of a neuromusculoskeletal system using divide and conquer type models | |
| Singh et al. | A unified approach for optimal dose delivery and trajectory optimization for the treatment of prostate cancer | |
| Cheong et al. | A proof-of-concept study for the real-time prediction of respiratory patterns: A simple bayesian approach |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |