CN116999090A - Image processing system and method for inferior vena cava measurement - Google Patents
Image processing system and method for inferior vena cava measurement Download PDFInfo
- Publication number
- CN116999090A CN116999090A CN202310978392.8A CN202310978392A CN116999090A CN 116999090 A CN116999090 A CN 116999090A CN 202310978392 A CN202310978392 A CN 202310978392A CN 116999090 A CN116999090 A CN 116999090A
- Authority
- CN
- China
- Prior art keywords
- ivc
- vena cava
- image
- inferior vena
- frame
- 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.)
- Pending
Links
- 210000001631 vena cava inferior Anatomy 0.000 title claims abstract description 97
- 238000005259 measurement Methods 0.000 title claims abstract description 46
- 238000012545 processing Methods 0.000 title claims abstract description 28
- 238000000034 method Methods 0.000 title claims abstract description 13
- 230000008859 change Effects 0.000 claims abstract description 51
- 238000004364 calculation method Methods 0.000 claims abstract description 20
- 238000007781 pre-processing Methods 0.000 claims abstract description 16
- 230000017531 blood circulation Effects 0.000 claims description 50
- 239000000523 sample Substances 0.000 claims description 37
- 210000004204 blood vessel Anatomy 0.000 claims description 23
- 238000005070 sampling Methods 0.000 claims description 22
- 239000012528 membrane Substances 0.000 claims description 18
- 230000002093 peripheral effect Effects 0.000 claims description 18
- 238000002604 ultrasonography Methods 0.000 claims description 12
- 238000005516 engineering process Methods 0.000 claims description 9
- 230000029058 respiratory gaseous exchange Effects 0.000 claims description 9
- 210000004185 liver Anatomy 0.000 claims description 8
- 238000003708 edge detection Methods 0.000 claims description 7
- 238000006073 displacement reaction Methods 0.000 claims description 6
- 238000009499 grossing Methods 0.000 claims description 6
- 230000002440 hepatic effect Effects 0.000 claims description 6
- 230000001746 atrial effect Effects 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 210000002989 hepatic vein Anatomy 0.000 claims description 3
- 230000009467 reduction Effects 0.000 claims description 3
- 239000007788 liquid Substances 0.000 description 7
- 238000012544 monitoring process Methods 0.000 description 4
- 241001270131 Agaricus moelleri Species 0.000 description 3
- 238000003384 imaging method Methods 0.000 description 3
- 210000001519 tissue Anatomy 0.000 description 3
- 208000028399 Critical Illness Diseases 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000003672 processing method Methods 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- 206010016803 Fluid overload Diseases 0.000 description 1
- 230000003187 abdominal effect Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 230000003205 diastolic effect Effects 0.000 description 1
- 238000003113 dilution method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 210000003374 extravascular lung water Anatomy 0.000 description 1
- 206010016766 flatulence Diseases 0.000 description 1
- 230000000004 hemodynamic effect Effects 0.000 description 1
- 238000001802 infusion Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000000968 intestinal effect Effects 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000010412 perfusion Effects 0.000 description 1
- 238000003825 pressing Methods 0.000 description 1
- 238000004393 prognosis Methods 0.000 description 1
- 230000009257 reactivity Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000241 respiratory effect Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 210000003462 vein Anatomy 0.000 description 1
- 210000002417 xiphoid bone Anatomy 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
- A61B8/0891—Detecting organic movements or changes, e.g. tumours, cysts, swellings for diagnosis of blood vessels
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5269—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving detection or reduction of artifacts
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5269—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving detection or reduction of artifacts
- A61B8/5276—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving detection or reduction of artifacts due to motion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10132—Ultrasound image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Medical Informatics (AREA)
- Radiology & Medical Imaging (AREA)
- Molecular Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Heart & Thoracic Surgery (AREA)
- Pathology (AREA)
- Biophysics (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Biomedical Technology (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Vascular Medicine (AREA)
- Quality & Reliability (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Ultra Sonic Daignosis Equipment (AREA)
Abstract
The application discloses an image processing system and method for measuring inferior vena cava, which particularly relates to the clinical field, and comprises an IVC image acquisition module, an IVC image preprocessing module, an IVC automatic positioning measurement module and an IVC motion change calculation module.
Description
Technical Field
The application relates to the technical field of clinic, in particular to an image processing system and method for inferior vena cava measurement.
Background
The inferior vena cava is one of the main veins in the human body, and measuring the diameter and flow rate of the inferior vena cava has important significance for medical diagnosis and monitoring of patient conditions, and currently, the inferior vena cava is usually measured by an ultrasonic imaging technology, however, the conventional ultrasonic imaging equipment has some difficulties and disadvantages in practical application, such as complex operation, huge instrument volume, high requirements on the technical level of operators and the like.
Scanning the inferior vena cava of a patient by using ultrasonic equipment, generating a series of image data, preprocessing the acquired image data to obtain a new IVC multi-frame ultrasonic image, positioning the inferior vena cava region by adopting an edge detection technology, detecting the edge of the inferior vena cava by a canny algorithm to obtain the upper wall and the lower wall of the blood vessel of the inferior vena cava, determining the angles of the upper arm and the lower wall of the blood vessel, generating and displaying a inferior vena cava sampling line, calculating the blood flow change coefficients of different positions of the inferior vena cava by a formula, further determining the cross section of the inferior vena cava, designing the cross section of the inferior vena cava by taking P0 as the center of a circle, increasing step by step, calculating the standard deviation of the gray scale of each pixel in the circle every step, and moving the circle in the opposite direction until the circle contacts the edge and the edge until the outer diameter of the circle is the diameter of the IVC, and further calculating the continuous change condition of the IVC diameter in each frame of image by the formula.
The liquid treatment is used for recovering and maintaining tissue perfusion, is part of the conventional treatment of almost all critically ill patients, however, volume overload caused by excessive liquid infusion can have serious negative influence on prognosis of the patients, a large amount of liquid is infused for liquid resuscitation in the initial stage of liquid resuscitation of the critically ill patients, once hemodynamic monitoring is available, the liquid treatment is optimized through capacity state and liquid reactivity evaluation of the patients, and once the blood flow is mainly clinically evaluated in a mode of monitoring central venous pressure, thermal dilution method, full diastolic end-stage volume, stroke volume variability, extravascular lung water and the like, but the monitoring modes are all invasive operation, and the technology of measuring the diameter of the inferior vena cava by ultrasound has no wound on the patients, is convenient to operate, is simple and easy to learn and is available in real time, and a plurality of researches have fully proved that the sensitivity and the specificity of the variability of the inferior vena cava to the capacity prediction are very high.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present application provide an image processing system and method for inferior vena cava measurement, so as to solve the above-mentioned problems in the prior art.
In order to achieve the above purpose, the present application provides the following technical solutions: an image processing system for inferior vena cava measurement, comprising:
IVC image acquisition module: acquiring multi-frame ultrasonic images of IVC (IVC) at the lower edge of the twelfth rib of the target patient through an ultrasonic phased array probe with the frequency range of 2.5-5.0 MHz;
IVC image preprocessing module: preprocessing the collected IVC multi-frame ultrasonic image, wherein the preprocessing is to clean and reduce noise of the IVC ultrasonic image;
the IVC automatic positioning and measuring module comprises an IVC automatic positioning unit and an IVC automatic measuring unit;
the IVC automatic positioning unit automatically positions the position of the cross section of the inferior vena cava according to the blood flow signal of the inferior vena cava, and generates and displays a inferior vena cava sampling line in each ultrasonic image;
the IVC automatic measurement unit is used for automatically extracting gray values on a lower vena cava sampling line in each ultrasonic image to generate an anatomical image of a lower vena cava, and determining lower vena cava parameters according to the anatomical image, wherein the lower vena cava parameters comprise a maximum inner diameter, a minimum inner diameter and a respiratory variation rate;
the IVC motion change calculation module comprises an IVC motion tracking unit and an IVC diameter change calculation unit;
the IVC motion tracking unit is used for tracking the motion change of IVC according to the inferior vena cava anatomical image;
the IVC diameter calculation unit is used for calculating the diameter of the inferior vena cava along with the respiration change in each frame according to the motion change of IVC.
Preferably, the IVC image acquisition module acquires an IVC multi-frame ultrasound image, which specifically includes:
the ultrasonic phased array probe with the frequency range of 2.5-5.0MHz is used for adjusting the ultrasound to a heart examination mode, the ultrasonic phased array probe is placed at the intersection of the lower edge of a rib and the axillary midline and is perpendicular to the long axis of the body of a target patient, the sliding probe finds a second hepatic portal, the cross section of the inferior vena cava is found through the second hepatic portal, the probe is rotated by 90 degrees, the long axis section of the inferior vena cava is found, the sliding probe finds the left hepatic vein and the long axis section of the VC, and the IVC is at the right atrial inlet, so that IVC multi-frame ultrasonic images are obtained.
Preferably, the IVC image preprocessing module performs noise reduction processing on the IVC multi-frame ultrasonic image through median filtering, and specifically includes:
dividing the IVC multi-frame ultrasonic image into a plurality of sub-image videos according to the number of frames through the obtained IVC multi-frame ultrasonic image, analyzing and numbering each sub-image video, and respectively marking as a 1 ，a 2 ，……，a n Extracting pixel values of the IVC multi-frame ultrasonic image through an image processing library to obtain the pixel values of the IVC multi-frame ultrasonic image, marking the pixel values as a (i, j) and b (i, j), and substituting a (i, j) and b (i, j) into a formula respectivelyWherein n is represented as the size of the IVC multi-frame ultrasound image block, i and j are respectively represented as indexes of pixel positions in the block, ">The value is close to 0, which indicates that the higher the similarity of IVC multi-frame ultrasonic image blocks is;
and respectively comparing every two adjacent sub-image video blocks to obtain similarity ratio values of every two adjacent sub-image video blocks, comparing the similarity ratio values of every two adjacent sub-image video blocks with a preset similarity threshold value of every two adjacent sub-image video blocks, if the phase difference is within a certain range, indicating that the adjacent sub-image video blocks contain no noise or can be ignored, otherwise, indicating that the adjacent sub-image video blocks possibly contain noise, estimating a noise model according to the sub-image video blocks with larger differences, carrying out noise smoothing treatment on the sub-image video blocks with larger differences through the noise model, and rearranging the treated sub-image video blocks to obtain a new IVC multi-frame ultrasonic image.
Preferably, the IVC automatic positioning unit determines a inferior vena cava cross section according to a inferior vena cava blood flow signal, and specifically includes:
the ultrasonic phased array probe is arranged at different positions of the inferior vena cava and is used for recording the blood flow velocity and flow change of the vena cava and the measurement starting time is t 1 The blood flow velocity at different positions of the inferior vena cava is respectively recorded as v 1 ，v 2 ，……，v n Substituting blood flow velocity and recording time of inferior vena cava into formulaThe method comprises the steps of, wherein alpha is expressed as a blood flow change coefficient of a certain position of a lower vena cava, delta t is expressed as a time interval from the beginning to the end of measurement, and as the blood flow of the lower vena cava is larger when the blood flow of the lower vena cava is close to a liver, the blood flow of the lower vena cava is smaller when the blood flow of the lower vena cava is further away from the liver, comparing the blood flow change coefficient of the certain position of the lower vena cava with a preset blood flow change coefficient threshold value of a cross section of the lower vena cava, outputting a comparison result, and finding out the position of the lower vena cava, namely the cross section of the lower vena cava, wherein the blood flow change coefficient of the certain position of the lower vena cava is similar to the preset blood flow change coefficient threshold value of the cross section of the lower vena cava.
Preferably, the generation of the IVC automatic positioning unit on the inferior vena cava sampling line specifically includes:
in the preprocessed IVC multi-frame ultrasonic image, an edge detection technology is adopted to locate a lower vena cava region, the lower vena cava region is separated from surrounding tissues, after the lower vena cava region is determined, the edge of the lower vena cava region is detected through a canny algorithm, the upper wall of a blood vessel and the lower wall of the lower vena cava are obtained, curve fitting is carried out on the detected upper wall of the blood vessel and the lower wall of the lower vena cava, the angles of the upper wall of the blood vessel and the lower wall of the blood vessel are determined, finally, the curve obtained through fitting is perpendicular to the angle of the upper wall of the blood vessel and the lower wall of the lower vena cava, and a lower vena sampling line is generated and displayed.
Preferably, the IVC automatic measurement unit determines the diameter of the IVC, specifically comprising:
taking P0 as a center of a circle, increasing step by step, calculating the standard deviation of the gray scales of each pixel in the circular ring every time the standard deviation is increased step by step, comparing the standard deviation with the gray scale difference of the previous step, when one direction of the circular ring is contacted with the edge, the standard deviation of the gray scales of the pixels is changed greatly, wherein the standard deviation of the gray scales of the pixels is increased by 50%, the circular ring is not increased any more but moves in the opposite direction, and the circular ring is circulated until the circular ring is contacted with the edge and the edge, the center of the circular ring is positioned on the edge line, and the contact point of the circular ring, the edge and the edge is P u ，p 1 The outer diameter of the ring is equal to the outer diameter of the edge, and the outer diameter of the ring is equal to the diameter of the edge, that is, the outer diameter of the ring is the diameter of the IVC.
Preferably, the IVC motion tracking unit specifically includes:
at p u And p 1 For reference points, two containing p are respectively generated u And p 1 Is denoted as w u And w 1 Wherein w is u And w 1 In the following NCC algorithm, the selection of sampling window is critical, the ratio of the peripheral membrane to the peripheral membrane is determined according to the size of the peripheral membrane covered by two points of the peripheral membrane and the size of the peripheral membrane covered by the peripheral membrane, and w is calculated by NCC algorithm u And w 1 Thereby acquiring motion and diameter variation of the IVC;
a group of one-dimensional signals, namely gray values on a straight line, are researched, a group of one-dimensional signals are selected to be used as reference and comparison respectively, the gray area is used for describing the overlapping between the two groups of signals, a moving window intercepts a part of reference signals or comparison signals, and the reference signals or the comparison signals are marked as f n And g n Wherein n is a sample index, n is not less than 1 and not more than M, M is the total sample amount, f n And g n Is defined as the NCC coefficient of (C)The reference window is [ u, u+w-1 ]]Where u is the origin of the reference window, where w is the window size, β is the deviation of the comparison window from the reference window, [ β ] 1 ，β 2 ]For the search amplitude determined from the physiological shift amplitude, based on NCC, the dynamic movement of the target in two dimensions is calculated as w u And w 1 For reference, the diameter of the IVC in each frame can be calculated.
Preferably, the calculation of the continuous variation of the IVC diameter with respiration in each frame of image specifically comprises:
let IVC diameter in first frame be gamma 1 The diameter of the IVC in the subsequent image frame is then determined by continuously superimposing w u And w 1 The displacement in the vertical direction is respectively denoted asNamely: /> Wherein (1)> Wherein, gamma t Expressed as the diameter of IVC in the t-th image frame,>and->Is w u And w 1 Is in the vertical direction.
In order to achieve the above purpose, the present application provides the following technical solutions: an image processing method for inferior vena cava measurement, which uses the image processing system for inferior vena cava measurement, comprises the following steps:
s1, acquiring an IVC multi-frame ultrasonic image at the intersection point of the lower edge of the twelfth rib of a target patient and the axillary midline through an ultrasonic phased array probe with the frequency range of 2.5-5.0 MHz;
s2, dividing the acquired multi-frame ultrasonic image into a plurality of sub-image videos according to the number of frames, calculating the similarity ratio of every two adjacent sub-image video blocks through a formula, comparing the similarity ratio of every two adjacent sub-image video blocks with a preset similarity threshold of every two adjacent sub-image video blocks, and performing noise smoothing on the image video blocks with larger difference to obtain a new IVC multi-frame ultrasonic image;
s3, in the preprocessed IVC multi-frame ultrasonic image, positioning a lower vena cava region by adopting an edge detection technology, starting to detect the edge of the lower vena cava by a canny algorithm to obtain the upper wall and the lower wall of a blood vessel of the lower vena cava, determining the angles of the upper wall and the lower wall of the blood vessel, and generating and displaying a lower vena cava sampling line perpendicular to a curve obtained by fitting;
s4, installing a flow velocity sensor on the ultrasonic phased array probe, placing the ultrasonic phased array probe at different positions of the inferior vena cava according to the displayed inferior vena cava sampling line, recording the blood flow velocity and the flow change of the inferior vena cava and the measurement starting time, calculating the blood flow change coefficients of the different positions of the inferior vena cava through a formula, and further determining the cross section of the inferior vena cava;
s5, according to the determined cross section of the inferior vena cava, setting P0 as a circle center, increasing step by step, calculating the standard deviation of each pixel gray in the circular ring every time the standard deviation is increased step by step, and when the standard deviation of the pixel gray is changed greatly, moving the circular ring in the opposite direction until the circular ring contacts with the edge and the edge, namely, the outer diameter of the circular ring is the diameter of IVC;
s6, p u And p 1 For reference points, two containing p are respectively generated u And p 1 Is denoted as w u And w 1 Calculation of w by NCC algorithm u And w 1 Thereby acquiring motion and diameter variation of the IVC;
s7, setting the IVC diameter in the first frame as gamma 1 The diameter of the IVC in the subsequent image frame is then determined by continuously superimposing w u And w 1 The displacement in the vertical direction is respectively denoted asWill->And substituting the formula to calculate the continuous change condition of the IVC diameter along with the respiration in each frame of image.
The application has the technical effects and advantages that:
1. the image processing system can accurately detect the shape and the characteristics of the inferior vena cava, provide high-precision measurement results, reduce measurement errors and improve measurement accuracy through accurate image processing.
2. The method has the advantages that the technical difficulty of measuring the inferior vena cava through the liver is high, a plurality of technical difficulties exist in clinical application, the shape and the characteristics of the inferior vena cava can be accurately detected during the liver inspection, a high-precision measurement result is provided, the measurement error can be reduced through accurate image processing, and the measurement accuracy is improved.
3. The inferior vena cava measurement of the present application is generally a non-invasive examination method, and the examination can be completed by using a non-invasive imaging technique such as ultrasound to acquire image data of the inferior vena cava without cutting the skin of the patient or using any endoscope or other instrument image processing system, and by slightly pressing the body surface of the patient.
4. The image acquisition means can make up for the limitation of the common inferior vena cava measurement method in clinic. The conventional method for acquiring the inferior vena cava under the xiphoid process can not be normally applied to patients with abdominal operation, severe intestinal flatulence and the like, and the ultrasonic phased array probe can make up for the defect.
Drawings
Fig. 1 is a schematic diagram of the module connection of the present application.
Fig. 2 is a process step diagram of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1, the present application provides an image processing system for inferior vena cava measurement, comprising: the device comprises an IVC image acquisition module, an IVC image preprocessing module, an IVC automatic positioning measurement module and an IVC movement change calculation module, wherein the IVC automatic positioning measurement module comprises an IVC automatic positioning unit and an IVC automatic measurement unit, and the IVC movement change calculation module comprises an IVC movement tracking unit and an IVC diameter change calculation unit.
The IVC image acquisition module is connected with the IVC image preprocessing module, the IVC image preprocessing module is connected with the IVC automatic positioning measurement module, and the IVC automatic positioning measurement module is connected with the IVC motion change calculation module.
And the IVC image acquisition module acquires multi-frame ultrasonic images of the IVC at the lower edge of the twelfth rib of the target patient through an ultrasonic phased array probe with the frequency range of 2.5-5.0 MHz.
Further, the IVC image acquisition module acquires an IVC multi-frame ultrasound image, which specifically includes:
the ultrasonic phased array probe with the frequency range of 2.5-5.0MHz is used for adjusting the ultrasound to a heart examination mode, the ultrasonic phased array probe is placed at the intersection of the lower edge of a rib and the axillary midline and is perpendicular to the long axis of the body of a target patient, the sliding probe finds a second hepatic portal, the cross section of the inferior vena cava is found through the second hepatic portal, the probe is rotated by 90 degrees, the long axis section of the inferior vena cava is found, the sliding probe finds the left hepatic vein and the long axis section of the VC, and the IVC is at the right atrial inlet, so that IVC multi-frame ultrasonic images are obtained.
The IVC image preprocessing module is used for preprocessing the collected IVC multi-frame ultrasonic image, and the preprocessing is used for cleaning and reducing noise of the IVC ultrasonic image.
Further, the IVC image preprocessing module performs noise reduction processing on the IVC multi-frame ultrasonic image through median filtering, and specifically includes:
dividing the IVC multi-frame ultrasonic image into a plurality of sub-image videos according to the number of frames through the obtained IVC multi-frame ultrasonic image, analyzing and numbering each sub-image video, and respectively marking as a 1 ，a 2 ，……，a n Extracting pixel values of the IVC multi-frame ultrasonic image through an image processing library to obtain the pixel values of the IVC multi-frame ultrasonic image, marking the pixel values as a (i, j) and b (i, j), and substituting a (i, j) and b (i, j) into a formula respectivelyWherein n is represented as the size of the IVC multi-frame ultrasound image block, i and j are respectively represented as indexes of pixel positions in the block, ">The value is close to 0, which indicates that the higher the similarity of IVC multi-frame ultrasonic image blocks is;
and respectively comparing every two adjacent sub-image video blocks to obtain similarity ratio values of every two adjacent sub-image video blocks, comparing the similarity ratio values of every two adjacent sub-image video blocks with a preset similarity threshold value of every two adjacent sub-image video blocks, if the phase difference is within a certain range, indicating that the adjacent sub-image video blocks contain no noise or can be ignored, otherwise, indicating that the adjacent sub-image video blocks possibly contain noise, estimating a noise model according to the sub-image video blocks with larger differences, carrying out noise smoothing treatment on the sub-image video blocks with larger differences through the noise model, and rearranging the treated sub-image video blocks to obtain a new IVC multi-frame ultrasonic image.
The IVC automatic positioning and measuring module comprises an IVC automatic positioning unit and an IVC automatic measuring unit.
The IVC automatic positioning unit automatically positions the position of the cross section of the inferior vena cava according to the blood flow signals of the inferior vena cava, and generates and displays inferior vena cava sampling lines in each ultrasonic image.
Further, the generation of the inferior vena cava sampling line in the IVC automatic positioning unit specifically includes:
in the preprocessed IVC multi-frame ultrasonic image, an edge detection technology is adopted to locate a lower vena cava region, the lower vena cava region is separated from surrounding tissues, after the lower vena cava region is determined, the edge of the lower vena cava region is detected through a canny algorithm, the upper wall of a blood vessel and the lower wall of the lower vena cava are obtained, curve fitting is carried out on the detected upper wall of the blood vessel and the lower wall of the lower vena cava, the angles of the upper wall of the blood vessel and the lower wall of the blood vessel are determined, finally, the curve obtained through fitting is perpendicular to the angle of the upper wall of the blood vessel and the lower wall of the lower vena cava, and a lower vena sampling line is generated and displayed.
In a preferred technical scheme of the application, the IVC automatic positioning unit determines a cross section of a inferior vena cava according to a blood flow signal of the inferior vena cava, and specifically comprises:
the ultrasonic phased array probe is arranged at different positions of the inferior vena cava and is used for recording the blood flow velocity and flow change of the vena cava and the measurement starting time is t 1 The blood flow velocity at different positions of the inferior vena cava is respectively recorded as v 1 ，v 2 ，……，v n Substituting blood flow velocity and recording time of inferior vena cava into formulaThe method comprises the steps of, wherein alpha is expressed as a blood flow change coefficient of a certain position of a lower vena cava, delta t is expressed as a time interval from the beginning to the end of measurement, and as the blood flow of the lower vena cava is larger when the blood flow of the lower vena cava is close to a liver, the blood flow of the lower vena cava is smaller when the blood flow of the lower vena cava is further away from the liver, comparing the blood flow change coefficient of the certain position of the lower vena cava with a preset blood flow change coefficient threshold value of a cross section of the lower vena cava, outputting a comparison result, and finding out the position of the lower vena cava, namely the cross section of the lower vena cava, wherein the blood flow change coefficient of the certain position of the lower vena cava is similar to the preset blood flow change coefficient threshold value of the cross section of the lower vena cava.
The IVC automatic measurement unit is used for automatically extracting gray values on a lower vena cava sampling line in each ultrasonic image to generate an anatomical image of the lower vena cava, and determining lower vena cava parameters according to the anatomical image, wherein the lower vena cava parameters comprise the diameter of the IVC.
Further, the IVC automatic measurement unit determines the diameter of the IVC, and specifically includes:
setting a ring with P0 as the center of the circle, increasing the ring step by step, calculating the standard deviation of each pixel gray in the ring every time the ring is increased step by step, comparing with the gray difference of the previous step, when one direction of the ring is contacted with the edge, the standard deviation of the pixel gray will change greatly, the standard deviation of the pixel gray is increased by 50%, the ring is not increased but moves in the opposite direction, and the cycle is performed until the ring is contacted with the edge and the edge, the center of the ring is on the edge line, the contact point of the ring with the edge and the edge uses P u ，p 1 The outer diameter of the ring is equal to the outer diameter of the edge, and the outer diameter of the ring is equal to the diameter of the edge, that is, the outer diameter of the ring is the diameter of the IVC.
The IVC motion change calculation module comprises an IVC motion tracking unit and an IVC diameter change calculation unit.
The IVC motion tracking unit is used for tracking the motion change of IVC according to the inferior vena cava anatomical image.
Further, the IVC motion tracking unit specifically includes:
at p u And p 1 For reference points, two containing p are respectively generated u And p 1 Is denoted as w u And w 1 Wherein w is u And w 1 In the following NCC algorithm, the selection of sampling window is critical, the ratio of the peripheral membrane to the peripheral membrane is determined according to the size of the peripheral membrane covered by two points of the peripheral membrane and the size of the peripheral membrane covered by the peripheral membrane, and w is calculated by NCC algorithm u And w 1 Thereby acquiring motion and diameter variation of the IVC;
a group of one-dimensional signals, namely gray values on a straight line, are researched, a group of one-dimensional signals are selected to be used as reference and comparison respectively, the gray area is used for describing the overlapping between the two groups of signals, a moving window intercepts a part of reference signals or comparison signals, and the reference signals or the comparison signals are marked as f n And g n Wherein n is a sample index, n is not less than 1 and not more than M, M is the total sample amount, f n And g n Is defined as the NCC coefficient of (C)The reference window is [ u, u+w-1 ]]Where u is the origin of the reference window, where w is the window size, β is the deviation of the comparison window from the reference window, [ β ] 1 ，β 2 ]For the search amplitude determined from the physiological shift amplitude, based on NCC, the dynamic movement of the target in two dimensions is calculated as w u And w 1 For reference, the diameter of the IVC in each frame can be calculated.
The IVC diameter calculation unit is used for calculating the diameter of the inferior vena cava along with the respiration change in each frame according to the motion change of IVC.
Further, the IVC diameter calculation unit calculates continuous variation of the IVC diameter along with respiration in each frame of image, and specifically includes:
let IVC diameter in first frame be gamma 1 Then, IVC is performed on the subsequent imageThe diameter in the frame is determined by continuously superimposing w u And w 1 The displacement in the vertical direction is respectively denoted asNamely: /> Wherein (1)> Wherein, gamma t Expressed as the diameter of IVC in the t-th image frame,>and->Is w u And w 1 Is in the vertical direction.
The present embodiment as shown in fig. 2 provides an image processing method for inferior vena cava measurement, which includes the following steps:
s1, acquiring an IVC multi-frame ultrasonic image at the intersection point of the lower edge of the twelfth rib of a target patient and the axillary midline through an ultrasonic phased array probe with the frequency range of 2.5-5.0 MHz;
s2, dividing the acquired multi-frame ultrasonic image into a plurality of sub-image videos according to the number of frames, calculating the similarity ratio of every two adjacent sub-image video blocks through a formula, comparing the similarity ratio of every two adjacent sub-image video blocks with a preset similarity threshold of every two adjacent sub-image video blocks, and performing noise smoothing on the image video blocks with larger difference to obtain a new IVC multi-frame ultrasonic image;
s3, in the preprocessed IVC multi-frame ultrasonic image, positioning a lower vena cava region by adopting an edge detection technology, starting to detect the edge of the lower vena cava by a canny algorithm to obtain the upper wall and the lower wall of a blood vessel of the lower vena cava, determining the angles of the upper wall and the lower wall of the blood vessel, and generating and displaying a lower vena cava sampling line perpendicular to a curve obtained by fitting;
s4, installing a flow velocity sensor on the ultrasonic phased array probe, placing the ultrasonic phased array probe at different positions of the inferior vena cava according to the displayed inferior vena cava sampling line, recording the blood flow velocity and the flow change of the inferior vena cava and the measurement starting time, calculating the blood flow change coefficients of the different positions of the inferior vena cava through a formula, and further determining the cross section of the inferior vena cava;
s5, according to the determined cross section of the inferior vena cava, setting P0 as a circle center, increasing step by step, calculating the standard deviation of each pixel gray in the circular ring every time the standard deviation is increased step by step, and when the standard deviation of the pixel gray is changed greatly, moving the circular ring in the opposite direction until the circular ring contacts with the edge and the edge, namely, the outer diameter of the circular ring is the diameter of IVC;
s6, p u And p 1 For reference points, two containing p are respectively generated u And p 1 Is denoted as w u And w 1 Calculation of w by NCC algorithm u And w 1 Thereby acquiring motion and diameter variation of the IVC;
s7, setting the IVC diameter in the first frame as gamma 1 The diameter of the IVC in the subsequent image frame is then determined by continuously superimposing w u And w 1 The displacement in the vertical direction is respectively denoted asWill->And substituting the formula to calculate the continuous change condition of the IVC diameter along with the respiration in each frame of image.
Finally: the foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (9)
1. An image processing system for inferior vena cava measurement, comprising:
IVC image acquisition module: acquiring multi-frame ultrasonic images of IVC (IVC) at the lower edge of the twelfth rib of the target patient through an ultrasonic phased array probe with the frequency range of 2.5-5.0 MHz;
IVC image preprocessing module: preprocessing the collected IVC multi-frame ultrasonic image, wherein the preprocessing is to clean and reduce noise of the IVC ultrasonic image;
the IVC automatic positioning and measuring module comprises an IVC automatic positioning unit and an IVC automatic measuring unit;
the IVC automatic positioning unit automatically positions the position of the cross section of the inferior vena cava according to the blood flow signal of the inferior vena cava, and generates and displays a inferior vena cava sampling line in each ultrasonic image;
the IVC automatic measurement unit is used for automatically extracting gray values on a lower vena cava sampling line in each ultrasonic image to generate an anatomical image of a lower vena cava, and determining lower vena cava parameters according to the anatomical image, wherein the lower vena cava parameters comprise the diameter of IVC;
the IVC motion change calculation module comprises an IVC motion tracking unit and an IVC diameter change calculation unit;
the IVC motion tracking unit is used for tracking the motion change of IVC according to the inferior vena cava anatomical image;
the IVC diameter calculation unit is used for calculating the diameter of the inferior vena cava along with the respiration change in each frame according to the motion change of IVC.
2. The image processing system for inferior vena cava measurement according to claim 1, wherein the IVC image acquisition module acquires IVC multi-frame ultrasound images, specifically comprising:
the ultrasonic phased array probe with the frequency range of 2.5-5.0MHz is used for adjusting the ultrasound to a heart examination mode, the ultrasonic phased array probe is placed at the intersection of the lower edge of a rib and the axillary midline and is perpendicular to the long axis of the body of a target patient, the sliding probe finds a second hepatic portal, the cross section of the inferior vena cava is found through the second hepatic portal, the probe is rotated by 90 degrees, the long axis section of the inferior vena cava is found, the sliding probe finds the left hepatic vein and the long axis section of the VC, and the IVC is at the right atrial inlet, so that IVC multi-frame ultrasonic images are obtained.
3. The image processing system for inferior vena cava measurement according to claim 1, wherein the noise reduction processing is performed on the IVC multi-frame ultrasound image by median filtering, and specifically comprises:
dividing the IVC multi-frame ultrasonic image into a plurality of sub-image videos according to the number of frames through the obtained IVC multi-frame ultrasonic image, analyzing and numbering each sub-image video, and respectively marking as a 1 ，a 2 ，……，a n Extracting pixel values of the IVC multi-frame ultrasonic image through an image processing library to obtain the pixel values of the IVC multi-frame ultrasonic image, marking the pixel values as a (i, j) and b (i, j), and substituting a (i, j) and b (i, j) into a formula respectivelyWherein n is represented as the size of the IVC multi-frame ultrasound image block, i and j are respectively represented as indexes of pixel positions in the block, ">The value is close to 0, which indicates that the higher the similarity of IVC multi-frame ultrasonic image blocks is;
and respectively comparing every two adjacent sub-image video blocks to obtain similarity ratio values of every two adjacent sub-image video blocks, comparing the similarity ratio values of every two adjacent sub-image video blocks with a preset similarity threshold value of every two adjacent sub-image video blocks, if the phase difference is within a certain range, indicating that the adjacent sub-image video blocks contain no noise or can be ignored, otherwise, indicating that the adjacent sub-image video blocks possibly contain noise, estimating a noise model according to the sub-image video blocks with larger differences, carrying out noise smoothing treatment on the sub-image video blocks with larger differences through the noise model, and rearranging the treated sub-image video blocks to obtain a new IVC multi-frame ultrasonic image.
4. An image processing system for inferior vena cava measurement as claimed in claim 1, wherein determining the inferior vena cava cross section from the inferior vena cava blood flow signal comprises:
the ultrasonic phased array probe is arranged at different positions of the inferior vena cava and is used for recording the blood flow velocity and flow change of the vena cava and the measurement starting time is t 1 The blood flow velocity at different positions of the inferior vena cava is respectively recorded as v 1 ，v 2 ，……，v n Substituting blood flow velocity and recording time of inferior vena cava into formulaThe method comprises the steps of, wherein alpha is expressed as a blood flow change coefficient of a certain position of a lower vena cava, delta t is expressed as a time interval from the beginning to the end of measurement, and as the blood flow of the lower vena cava is larger when the blood flow of the lower vena cava is close to a liver, the blood flow of the lower vena cava is smaller when the blood flow of the lower vena cava is further away from the liver, comparing the blood flow change coefficient of the certain position of the lower vena cava with a preset blood flow change coefficient threshold value of a cross section of the lower vena cava, outputting a comparison result, and finding out the position of the lower vena cava, namely the cross section of the lower vena cava, wherein the blood flow change coefficient of the certain position of the lower vena cava is similar to the preset blood flow change coefficient threshold value of the cross section of the lower vena cava.
5. An image processing system for inferior vena cava measurement as in claim 1, wherein the generation of inferior vena cava sampling lines comprises:
in the preprocessed IVC multi-frame ultrasonic image, an edge detection technology is adopted to locate a lower vena cava region, the lower vena cava region is separated from surrounding tissues, after the lower vena cava region is determined, the edge of the lower vena cava region is detected through a canny algorithm, the upper wall of a blood vessel and the lower wall of the lower vena cava are obtained, curve fitting is carried out on the detected upper wall of the blood vessel and the lower wall of the lower vena cava, the angles of the upper wall of the blood vessel and the lower wall of the blood vessel are determined, finally, the curve obtained through fitting is perpendicular to the angle of the upper wall of the blood vessel and the lower wall of the lower vena cava, and a lower vena sampling line is generated and displayed.
6. The image processing system for inferior vena cava measurement according to claim 1, wherein determining the diameter of the IVC comprises:
setting a ring with P0 as the center of the circle, increasing the ring step by step, calculating the standard deviation of each pixel gray in the ring every time the ring is increased step by step, comparing with the gray difference of the previous step, when one direction of the ring is contacted with the edge, the standard deviation of the pixel gray will change greatly, the standard deviation of the pixel gray is increased by 50%, the ring is not increased but moves in the opposite direction, and the cycle is performed until the ring is contacted with the edge and the edge, the center of the ring is on the edge line, the contact point of the ring with the edge and the edge uses P u ，p 1 The outer diameter of the ring is equal to the outer diameter of the edge, and the outer diameter of the ring is equal to the diameter of the edge, that is, the outer diameter of the ring is the diameter of the IVC.
7. The image processing system for inferior vena cava measurement as in claim 1, wherein the IVC motion tracking unit comprises:
at p u And p 1 For reference points, two containing p are respectively generated u And p 1 Is denoted as w u And w 1 Wherein w is u And w 1 In the following NCC algorithm, the selection of sampling window is critical, the ratio of the peripheral membrane to the peripheral membrane is determined by the size of the peripheral membrane covered by two points of the peripheral membrane and the size of the peripheral membrane covered by the peripheral membrane, calculated by NCCCalculating w by method u And w 1 Thereby acquiring motion and diameter variation of the IVC;
a group of one-dimensional signals, namely gray values on a straight line, are researched, a group of one-dimensional signals are selected to be used as reference and comparison respectively, the gray area is used for describing the overlapping between the two groups of signals, a moving window intercepts a part of reference signals or comparison signals, and the reference signals or the comparison signals are marked as f n And g n Wherein n is a sample index, n is not less than 1 and not more than M, M is the total sample amount, f n And g n Is defined as the NCC coefficient of (C)(β 1 <β<β 2 ) The reference window is [ u, u+w-1 ]]Where u is the origin of the reference window, where w is the window size, β is the deviation of the comparison window from the reference window, [ β ] 1 ，β 2 ]For the search amplitude determined from the physiological shift amplitude, based on NCC, the dynamic movement of the target in two dimensions is calculated as w u And w 1 For reference, the diameter of the IVC in each frame can be calculated.
8. The image processing system for inferior vena cava measurement according to claim 1, wherein the calculation of IVC diameter continuously varying with respiration in each frame of image specifically comprises:
let IVC diameter in first frame be gamma 1 The diameter of the IVC in the subsequent image frame is then determined by continuously superimposing w u And w 1 The displacement in the vertical direction is respectively denoted asNamely: />) T=1, 2, … …, m, wherein->t＝1，2，……，m，/>t=1, 2, … …, m, wherein γ t Expressed as the diameter of IVC in the t-th image frame,>is w u And w 1 Is in the vertical direction.
9. A method of image processing of inferior vena cava measurements using an image processing system of inferior vena cava measurements as claimed in any one of claims 1-8, comprising the steps of:
s1, acquiring an IVC multi-frame ultrasonic image at the intersection point of the lower edge of the twelfth rib of a target patient and the axillary midline through an ultrasonic phased array probe with the frequency range of 2.5-5.0 MHz;
s2, dividing the acquired multi-frame ultrasonic image into a plurality of sub-image videos according to the number of frames, calculating the similarity ratio of every two adjacent sub-image video blocks through a formula, comparing the similarity ratio of every two adjacent sub-image video blocks with a preset similarity threshold of every two adjacent sub-image video blocks, and performing noise smoothing on the image video blocks with larger difference to obtain a new IVC multi-frame ultrasonic image;
s3, in the preprocessed IVC multi-frame ultrasonic image, positioning a lower vena cava region by adopting an edge detection technology, starting to detect the edge of the lower vena cava by a canny algorithm to obtain the upper wall and the lower wall of a blood vessel of the lower vena cava, determining the angles of the upper wall and the lower wall of the blood vessel, and generating and displaying a lower vena cava sampling line perpendicular to a curve obtained by fitting;
s4, installing a flow velocity sensor on the ultrasonic phased array probe, placing the ultrasonic phased array probe at different positions of the inferior vena cava according to the displayed inferior vena cava sampling line, recording the blood flow velocity and the flow change of the inferior vena cava and the measurement starting time, calculating the blood flow change coefficients of the different positions of the inferior vena cava through a formula, and further determining the cross section of the inferior vena cava;
s5, according to the determined cross section of the inferior vena cava, setting P0 as a circle center, increasing step by step, calculating the standard deviation of each pixel gray in the circular ring every time the standard deviation is increased step by step, and when the standard deviation of the pixel gray is changed greatly, moving the circular ring in the opposite direction until the circular ring contacts with the edge and the edge, namely, the outer diameter of the circular ring is the diameter of IVC;
s6, p u And p 1 For reference points, two containing p are respectively generated u And p 1 Is denoted as w u And w 1 Calculation of w by NCC algorithm u And w 1 Thereby acquiring motion and diameter variation of the IVC;
s7, setting the IVC diameter in the first frame as gamma 1 The diameter of the IVC in the subsequent image frame is then determined by continuously superimposing w u And w 1 The displacement in the vertical direction is respectively denoted asWill->And substituting the formula to calculate the continuous change condition of the IVC diameter along with the respiration in each frame of image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310978392.8A CN116999090A (en) | 2023-08-04 | 2023-08-04 | Image processing system and method for inferior vena cava measurement |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310978392.8A CN116999090A (en) | 2023-08-04 | 2023-08-04 | Image processing system and method for inferior vena cava measurement |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116999090A true CN116999090A (en) | 2023-11-07 |
Family
ID=88570606
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310978392.8A Pending CN116999090A (en) | 2023-08-04 | 2023-08-04 | Image processing system and method for inferior vena cava measurement |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116999090A (en) |
-
2023
- 2023-08-04 CN CN202310978392.8A patent/CN116999090A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP1875867B1 (en) | Ultrasound diagnosis apparatus and method of processing ultrasound data | |
| US7927278B2 (en) | Split-screen display system and standardized methods for ultrasound image acquisition and multi-frame data processing | |
| KR101334064B1 (en) | Apparatus and method for measureing velocity vector imaging of blood vessel | |
| US7856130B2 (en) | Object recognition system for medical imaging | |
| US20080051660A1 (en) | Methods and apparatuses for medical imaging | |
| Schiller et al. | Analysis of left ventricular systolic function | |
| CN108198174B (en) | Cardiovascular IVOCT and IVUS automatic registration method and device | |
| JP2014217745A (en) | Ultrasonic diagnostic apparatus and method of controlling the same | |
| CN101647716B (en) | Device for directly measuring blood flow velocity | |
| CN108053429B (en) | Automatic registration method and device for cardiovascular OCT and coronary angiography | |
| Knight et al. | Accuracy and test-retest reproducibility of two-dimensional knowledge-based volumetric reconstruction of the right ventricle in pulmonary hypertension | |
| US6909914B2 (en) | Method for generating time independent images of moving objects | |
| Crimi et al. | Automatic measurement of venous pressure using B-mode ultrasound | |
| US20220202376A1 (en) | Medical imaging apparatus including biological signal processing system, medical imaging system, and biological signal processing method | |
| US20130158403A1 (en) | Method for Obtaining a Three-Dimensional Velocity Measurement of a Tissue | |
| Fan et al. | Ultrasound measurement of brachial flow-mediated vasodilator response | |
| Wick et al. | Detection of cardiac quiescence from B-mode echocardiography using a correlation-based frame-to-frame deviation measure | |
| Hennersperger et al. | Vascular 3D+ T freehand ultrasound using correlation of doppler and pulse-oximetry data | |
| JP2003079627A (en) | Cardiac wall movement evaluation apparatus | |
| CN116999090A (en) | Image processing system and method for inferior vena cava measurement | |
| CN108720870A (en) | A kind of fatty liver detecting system based on ultrasonic attenuation coefficient | |
| CN116269496A (en) | Heart three-dimensional ultrasonic imaging and heart function evaluation system based on implicit neural representation | |
| CN115861132A (en) | Blood vessel image correction method, device, medium and equipment | |
| US20100081932A1 (en) | Ultrasound Volume Data Processing | |
| CN110931130B (en) | Method for evaluating respiratory and cardiac cycles based on B ultrasonic signals |
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 |