CN116473581A - Total knee replacement operation image inspection method and device - Google Patents
Total knee replacement operation image inspection method and device Download PDFInfo
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- CN116473581A CN116473581A CN202310423413.XA CN202310423413A CN116473581A CN 116473581 A CN116473581 A CN 116473581A CN 202310423413 A CN202310423413 A CN 202310423413A CN 116473581 A CN116473581 A CN 116473581A
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- 238000013150 knee replacement Methods 0.000 title claims abstract description 23
- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000007689 inspection Methods 0.000 title claims description 11
- 239000002184 metal Substances 0.000 claims abstract description 39
- 239000013598 vector Substances 0.000 claims abstract description 22
- 238000001356 surgical procedure Methods 0.000 claims description 15
- 238000000605 extraction Methods 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 4
- 238000004891 communication Methods 0.000 claims description 3
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 210000001930 leg bone Anatomy 0.000 abstract description 9
- 238000002591 computed tomography Methods 0.000 description 15
- 210000002414 leg Anatomy 0.000 description 4
- 238000005452 bending Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 206010066902 Surgical failure Diseases 0.000 description 1
- 210000000988 bone and bone Anatomy 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000005251 gamma ray Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
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- 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
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/03—Computed tomography [CT]
- A61B6/032—Transmission computed tomography [CT]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
- A61B6/505—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for diagnosis of bone
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
- A61B6/5205—Devices using data or image processing specially adapted for radiation diagnosis involving processing of raw data to produce diagnostic data
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
- A61B6/5294—Devices using data or image processing specially adapted for radiation diagnosis involving using additional data, e.g. patient information, image labeling, acquisition parameters
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/187—Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
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- 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
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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Abstract
A full knee replacement operation image checking method and device, read in the specialized CT image of DCM, namely CT image with metal pole, obtain the maximum gray value and minimum gray value of the image, take the part above 75% of the gray value, these parts include metal pole and some scattered points, use the maximum connected threshold to extract the point outside the metal pole, the image only has metal pole at this moment, binarize the image, obtain the number of layers of the image, height of the image and space height of a layer, calculate how many layers of images are in 10mm, take the central point once every 10mm of layers in the total number of layers, calculate the vector of adjacent points, make the subtraction between the adjacent vectors is the error, define a reasonable scope, all errors are qualified in the scope, otherwise are disqualified. Therefore, the error rate of planning and osteotomy navigation according to unqualified pictures in the later period can be reduced, the leg bones of the pictures are consistent with the leg bones of patients, and the time of manual judgment is reduced.
Description
Technical Field
The invention relates to the technical field of medical image processing, in particular to an image inspection method and an image inspection device for total knee replacement surgery.
Background
CT (Computed Tomography) it uses precisely collimated X-ray beam, gamma ray, ultrasonic wave, etc. to scan the cross section around a certain part of human body together with a detector with very high sensitivity.
Prior to total knee replacement surgery, a physician may perform a pre-operative planning from CT pictures of the patient. The patient may move his or her legs during CT taking due to pain or other reasons, which may cause the CT pictures taken to deviate from each other. Planning and osteotomy navigation are performed according to unqualified pictures, so that the error rate is increased, and surgical failure can be caused.
Disclosure of Invention
In order to overcome the defects of the prior art, the technical problem to be solved by the invention is to provide the image checking method for the total knee replacement surgery, which can reduce the error rate of planning and osteotomy navigation according to unqualified pictures in the later period, ensure that the leg bones of the pictures are consistent with the leg bones of patients, and reduce the time of manual judgment.
The technical scheme of the invention is as follows: the image checking method for the total knee replacement operation comprises the following steps:
(1) Reading in a CT image of a professional DCM;
(2) Obtaining a maximum gray value and a minimum gray value of an image;
(3) Taking more than 75% of gray values, wherein the parts comprise metal rods and some scattered points;
(4) Removing points other than the metal rods by using maximum connected threshold extraction, wherein the image only contains the metal rods; the maximum connected threshold is provided by binarizing the upper image, setting more than 75% as 1, setting the other images as 0, traversing the whole image, calculating the number of adjacent points and the number of adjacent areas according to the coordinates of each point, sequencing the sizes of the adjacent areas from large to small, and taking the largest area;
(5) Binarizing the image;
(6) Acquiring the number of layers of an image, the height of the image and the space height of one layer;
(7) Calculating how many layers of images are in 10 mm;
(8) Taking a central point once every 10mm of the total layers;
(9) Calculating the vector of the adjacent point;
(10) The subtraction between adjacent vectors is the error;
(11) Defining a reasonable range;
(12) All errors are qualified within the range, otherwise, the errors are unqualified.
Before the whole knee replacement operation is planned, a CT picture is taken on the leg, and a metal rod is bound, the invention reads in a professional CT image of DCM, namely the CT image with the metal rod, acquires the maximum gray value and the minimum gray value of the image, acquires more than 75% of the gray value, the parts comprise the metal rod and some scattered points, uses the maximum connected threshold extraction to remove the points except the metal rod, only the metal rod is used for the image, binarizes the image, acquires the layer number of the image, the height of the image and the space height of one layer, calculates how many layers of the image are in 10mm, takes a central point every 10mm of the total layer number, calculates the vector of the adjacent points, and makes subtraction between the adjacent vectors to be an error, defines a reasonable range, and if not, all the errors are qualified in the range. That is, the picture can be said to be acceptable as long as the metal bar is inspected to be normal without bending deformation or the like. Therefore, the error rate of planning and osteotomy navigation according to unqualified pictures in the later period can be reduced, the leg bones of the pictures are consistent with the leg bones of patients, and the time of manual judgment is reduced.
Also provided is an image inspection device for total knee replacement surgery, comprising:
a data reading module configured to read in a CT image of a professional DCM;
the data processing module acquires a maximum gray value and a minimum gray value of an image, takes more than 75% of the gray values, the parts comprise metal rods and some scattered points, and uses a maximum communication threshold extraction to remove points except the metal rods, so that only the metal rods are used for the image, and the image is binarized;
the error calculation module is configured to acquire the number of layers of the image, the height of the image and the space height of one layer, calculate how many layers of images exist in 10mm, take a central point every 10mm of the total number of layers, calculate the vectors of adjacent points, and make subtraction between the adjacent vectors to be the error;
and the judging module is configured to define a reasonable range, and all errors are qualified within the range, or else, are unqualified.
Drawings
Fig. 1 is a flow chart illustrating an image inspection method for total knee replacement according to the present invention.
Detailed Description
As shown in fig. 1, this total knee replacement surgery image inspection method includes the steps of:
(1) Reading in a CT image of a professional DCM;
(2) Obtaining a maximum gray value and a minimum gray value of an image;
(3) Taking more than 75% of gray values, wherein the parts comprise metal rods and some scattered points;
the gray scale value of the metal rod is larger than that of the human bone, so that the gray scale value of the metal rod can be basically included by taking more than 75% of the gray scale value. This operation is to extract the metal rod from the whole image.
(4) Removing points other than the metal rods by using maximum connected threshold extraction, wherein the image only contains the metal rods; the maximum connected threshold is provided by binarizing the upper image, setting more than 75% as 1, setting the other images as 0, traversing the whole image, calculating the number of adjacent points and the number of adjacent areas according to the coordinates of each point, sequencing the sizes of the adjacent areas from large to small, and taking the largest area;
(5) Binarizing the image;
(6) Acquiring the number of layers of an image, the height of the image and the space height of one layer;
(7) Calculating how many layers of images are in 10 mm;
(8) Taking a central point once every 10mm of the total layers;
(9) Calculating the vector of the adjacent point;
(10) The subtraction between adjacent vectors is the error;
(11) Defining a reasonable range (the range should be determined by a large number of experiments, the error is within a normal range, the image offset can be normally applied, and finally, the error calculated before and the defined range are used for judging);
(12) All errors are qualified within the range, otherwise, the errors are unqualified.
Before the whole knee replacement operation is planned, a CT picture is taken on the leg, and a metal rod is bound, the invention reads in a professional CT image of DCM, namely the CT image with the metal rod, acquires the maximum gray value and the minimum gray value of the image, acquires more than 75% of the gray value, the parts comprise the metal rod and some scattered points, uses the maximum connected threshold extraction to remove the points except the metal rod, only the metal rod is used for the image, binarizes the image, acquires the layer number of the image, the height of the image and the space height of one layer, calculates how many layers of the image are in 10mm, takes a central point every 10mm of the total layer number, calculates the vector of the adjacent points, and makes subtraction between the adjacent vectors to be an error, defines a reasonable range, and if not, all the errors are qualified in the range. That is, the picture can be said to be acceptable as long as the metal bar is inspected to be normal without bending deformation or the like. Therefore, the error rate of planning and osteotomy navigation according to unqualified pictures in the later period can be reduced, the leg bones of the pictures are consistent with the leg bones of patients, and the time of manual judgment is reduced.
Preferably, in the step (5), the image background is changed to 0, and the object is changed to 1, so as to facilitate the following calculation.
Preferably, in the step (7), the height of one layer of the image=the total height of the image/the total number of layers of the image, and the target number of layers within 10 mm=10/the height of one layer of the image.
Preferably, in the step (8), the dots are taken at intervals of the same distance, and the smaller the distance is, the more accurate the distance is, but not less than the height of one layer of the image.
Preferably, in the step (8), the distance is 10mm.
Preferably, the adjacent points extracted in the step (9) are used as vectors, so as to obtain a plurality of vectors connected in space.
Preferably, in the step (10), if the metal rod is completely straight, the error is 0. However, when the leg bones are scanned, the human body breathes or the outside condition can cause the patient to have slight action in the middle of scanning, the small-amplitude action can not influence the use of the image, but the application of the image is problematic due to the overlarge action amplitude. Causing the image to be non-conforming to the patient's leg.
Preferably, in the step (12), the user is informed whether the error is out of range.
It will be understood by those skilled in the art that all or part of the steps in implementing the above embodiment method may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, where the program when executed includes the steps of the above embodiment method, and the storage medium may be: ROM/RAM, magnetic disks, optical disks, memory cards, etc. Accordingly, the present invention also includes, corresponding to the method of the present invention, an image examination apparatus for total knee replacement surgery, which is generally represented in the form of functional blocks corresponding to the steps of the method. The device comprises:
a data reading module configured to read in a CT image of a professional DCM;
the data processing module acquires a maximum gray value and a minimum gray value of an image, takes more than 75% of the gray values, the parts comprise metal rods and some scattered points, and uses a maximum communication threshold extraction to remove points except the metal rods, so that only the metal rods are used for the image, and the image is binarized;
the error calculation module is configured to acquire the number of layers of the image, the height of the image and the space height of one layer, calculate how many layers of images exist in 10mm, take a central point every 10mm of the total number of layers, calculate the vectors of adjacent points, and make subtraction between the adjacent vectors to be the error;
and the judging module is configured to define a reasonable range, and all errors are qualified within the range, or else, are unqualified.
Preferably, in the error calculation module, the height of one layer of the image=the total height of the image/the total layer of the image, the target layer number within 10 mm=10/the height of one layer of the image, the points are taken at equal intervals, and the smaller the distance, the more accurate the distance is, but not less than the height of one layer of the image.
The present invention is not limited to the preferred embodiments, but can be modified in any way according to the technical principles of the present invention, and all such modifications, equivalent variations and modifications are included in the scope of the present invention.
Claims (10)
1. The image inspection method for the total knee replacement operation is characterized in that: which comprises the following steps:
(1) Reading in a CT image of a professional DCM;
(2) Obtaining a maximum gray value and a minimum gray value of an image;
(3) Taking more than 75% of gray values, wherein the parts comprise metal rods and some scattered points;
(4) Removing points other than the metal rods by using maximum connected threshold extraction, wherein the image only contains the metal rods; the maximum connected threshold is provided by binarizing the upper image, setting more than 75% as 1, setting the other images as 0, traversing the whole image, calculating the number of adjacent points and the number of adjacent areas according to the coordinates of each point, sequencing the sizes of the adjacent areas from large to small, and taking the largest area;
(5) Binarizing the image;
(6) Acquiring the number of layers of an image, the height of the image and the space height of one layer;
(7) Calculating how many layers of images are in 10 mm;
(8) Taking a central point once every 10mm of the total layers;
(9) Calculating the vector of the adjacent point;
(10) The subtraction between adjacent vectors is the error;
(11) Defining a reasonable range;
(12) All errors are qualified within the range, otherwise, the errors are unqualified.
2. The method for examining an image of a total knee replacement surgery according to claim 1, wherein: in the step (5), the image background is changed to 0 and the target is changed to 1.
3. The method for examining an image of a total knee replacement surgery according to claim 2, wherein: in the step (7), the height of one image layer=the total height of the image/the total number of image layers, and the target number of layers within 10 mm=10/the height of one image layer.
4. A total knee replacement surgery image inspection method according to claim 3, wherein: in the step (8), the dots are taken at intervals of the same distance, and the smaller the distance is, the more accurate the distance is, but not less than the height of one layer of the image.
5. A total knee replacement surgery image inspection method according to claim 3, wherein: in the step (8), the distance is 10mm.
6. The method for examining an image of a total knee replacement surgery according to claim 4, wherein: and (3) vector the adjacent points extracted in the step (9) to obtain a plurality of vectors connected in space.
7. The method for image examination of total knee replacement surgery according to claim 5, wherein: in the step (10), if the metal rod is completely straight, the error is 0.
8. The method for examining an image of a total knee replacement surgery according to claim 6, wherein: in the step (12), the error is indicated to the user whether the error is out of range.
9. The apparatus for an image inspection method for total knee replacement surgery according to claim 1, wherein: it comprises the following steps:
a data reading module configured to read in a CT image of a professional DCM;
the data processing module acquires a maximum gray value and a minimum gray value of an image, takes more than 75% of the gray values, the parts comprise metal rods and some scattered points, and uses a maximum communication threshold extraction to remove points except the metal rods, so that only the metal rods are used for the image, and the image is binarized;
the error calculation module is configured to acquire the number of layers of the image, the height of the image and the space height of one layer, calculate how many layers of images exist in 10mm, take a central point every 10mm of the total number of layers, calculate the vectors of adjacent points, and make subtraction between the adjacent vectors to be the error;
and the judging module is configured to define a reasonable range, and all errors are qualified within the range, or else, are unqualified.
10. The apparatus for the total knee replacement surgery image checking method according to claim 9, wherein: in the error calculation module, the height of one image layer = total image height/total image layer number, the target layer number within 10mm = 10/height of one image layer, the points are taken at equal intervals, and the smaller the distance, the more accurate the distance, but not less than the height of one image layer.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310423413.XA CN116473581A (en) | 2023-04-19 | 2023-04-19 | Total knee replacement operation image inspection method and device |
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| CN202310423413.XA CN116473581A (en) | 2023-04-19 | 2023-04-19 | Total knee replacement operation image inspection method and device |
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| CN202310423413.XA Pending CN116473581A (en) | 2023-04-19 | 2023-04-19 | Total knee replacement operation image inspection method and device |
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