CN113034441A - Arteriovenous point extraction method based on CTP image - Google Patents
Arteriovenous point extraction method based on CTP image Download PDFInfo
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- CN113034441A CN113034441A CN202110236884.0A CN202110236884A CN113034441A CN 113034441 A CN113034441 A CN 113034441A CN 202110236884 A CN202110236884 A CN 202110236884A CN 113034441 A CN113034441 A CN 113034441A
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- 238000000605 extraction Methods 0.000 title claims abstract description 14
- 210000001367 artery Anatomy 0.000 claims abstract description 63
- 210000003462 vein Anatomy 0.000 claims abstract description 47
- 238000012216 screening Methods 0.000 claims abstract description 15
- 238000000034 method Methods 0.000 claims abstract description 13
- 210000004204 blood vessel Anatomy 0.000 claims abstract description 12
- 210000004556 brain Anatomy 0.000 claims abstract description 12
- 238000001914 filtration Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 4
- 230000003788 cerebral perfusion Effects 0.000 description 4
- 230000017531 blood circulation Effects 0.000 description 2
- 239000002872 contrast media Substances 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 208000006011 Stroke Diseases 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000003727 cerebral blood flow Effects 0.000 description 1
- 206010008118 cerebral infarction Diseases 0.000 description 1
- 208000026106 cerebrovascular disease Diseases 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000013399 early diagnosis Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 210000000869 occipital lobe Anatomy 0.000 description 1
- 230000010412 perfusion Effects 0.000 description 1
- 238000004393 prognosis Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000002537 thrombolytic effect Effects 0.000 description 1
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- 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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
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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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- 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
- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
- G06T2207/20104—Interactive definition of region of interest [ROI]
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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
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
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Abstract
The invention discloses a method for extracting arteriovenous points based on a CTP image, which comprises the following steps: s1, obtaining a blood vessel region image; s2, screening out a vein region by using a 1/4 region under a brain region; s3, extracting the brightest point in the vein area as a vein point, and calculating a vein curve; s4, setting a time threshold according to the vein phase, and screening out an artery candidate region according to the time threshold; s5, carrying out space position constraint of registration on the artery candidate region to obtain an artery region; and S6, extracting the brightest point in the artery area as an artery point, and calculating an artery curve. The invention realizes the high-automatic and high-accuracy extraction of the artery and the vein in the CTP image by combining clinical experience and physiological and anatomical knowledge.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a method for extracting arteriovenous points based on a CTP image.
Background
CTP brain perfusion imaging is used as a very important imaging tool in the process of stroke diagnosis and treatment, and is an effective means for early diagnosis of cerebral infarction, guidance of emergency thrombolysis treatment and judgment of prognosis. The cerebral perfusion parameter map can accurately reflect blood flow parameters such as cerebral blood flow volume, contrast agent average passing time, contrast agent peak time and the like, thereby evaluating the cerebral perfusion state. For extraction of arteriovenous positions in a CTP cerebral perfusion image, the existing method mainly utilizes information carried in the CTP cerebral perfusion image to carry out extraction analysis so as to identify the positions of arteriovenous, but because the image acquisition process is easily influenced by external factors such as environment, machine performance and the like, the arteriovenous extraction method based on the image is easy to generate false positive, and the accuracy rate is not high enough.
Disclosure of Invention
In order to solve the problems, the invention provides a method for extracting arteriovenous points based on a CTP image, which is used for improving the accuracy of arteriovenous extraction in the CTP image.
The invention adopts the following technical scheme:
a method for extracting arteriovenous points based on a CTP image comprises the following steps:
s1, obtaining a blood vessel region image;
s2, screening out a vein region by using a 1/4 region under a brain region;
s3, extracting the brightest point in the vein area as a vein point, and calculating a vein curve;
s4, setting a time threshold according to the vein phase, and screening out an artery candidate region according to the time threshold;
s5, carrying out space position constraint of registration on the artery candidate region to obtain an artery region;
and S6, extracting the brightest point in the artery area as an artery point, and calculating an artery curve.
Further, the step S2 is specifically implemented by the following steps:
s21, selecting a region with the time sequence change rate of 20-40 and the CT value higher than 150-200Hu in the blood vessel region image as a vein candidate region;
s22, acquiring a time series ID corresponding to the maximum CT value of the vein candidate region;
s23, screening out images which are larger than or equal to the time series ID and contain the vein candidate region, and filtering out the region corresponding to the 1/4 region under the brain region in the images to obtain the vein region.
Further, when the vein curve is calculated, a weighted average calculation is performed on an area near a brightest point in the vein area, so that the vein curve is obtained.
Further, the step S4 is specifically: and acquiring the peak time of the vein point as a time threshold, and filtering all the time threshold and the subsequent areas to obtain the artery candidate area.
Further, the time threshold is taken to be the first 2s of the venous phase time.
Further, step S4 is specifically implemented by the following steps:
s41, obtaining an artery registration map, namely a brain blood vessel region map containing clinical standards of artery registration regions, wherein the artery registration regions comprise a middle artery registration region and an anterior artery registration region;
s42, comparing the artery registration map, and screening out the middle artery and the anterior artery areas from the artery candidate areas as artery areas.
Further, when the arterial curve is calculated, the area near the brightest point in the arterial area is taken to perform weighted average calculation, so that the arterial curve is obtained.
After adopting the technical scheme, compared with the background technology, the invention has the following advantages:
when extracting veins, the method filters partial regions by combining the time sequence ID of the maximum CT value and the clinical blood vessel distribution characteristics of 1/4 regions below the brain region, namely the occipital lobe region, so as to obtain the vein region; when an artery is extracted, a time threshold is set by combining with the clinical CTP image acquisition experience to serve as a screening standard of an artery candidate region, and then a middle artery region and an anterior artery region are further screened according to the physiological and anatomical knowledge, so that an artery region is determined; by combining clinical experience and physiological and anatomical knowledge, the method realizes the high-automatic and high-accuracy extraction of arteriovenous in the CTP image.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Examples
As shown in fig. 1, a method for extracting arteriovenous points based on a CTP image includes the following steps:
s1, obtaining a blood vessel region image; the region with the time series change rate larger than 0 indicates that blood flows through, and can be regarded as a blood vessel region.
S2, screening out a vein region by using a 1/4 region under a brain region;
the step S2 is specifically realized by the following steps:
s21, selecting a region with the time sequence change rate of 20-40 and the CT value higher than 150-200Hu in the blood vessel region image as a vein candidate region;
s22, acquiring a time series ID corresponding to the maximum CT value of the vein candidate region;
s23, screening out images which are larger than or equal to the time series ID and contain the vein candidate region, and filtering out the region corresponding to the 1/4 region under the brain region in the images to obtain the vein region.
S3, extracting the brightest point in the vein area as a vein point, and calculating a vein curve;
and when the vein curve is calculated, the weighted average calculation is carried out on the area near the brightest point in the vein area, so that the vein curve is obtained.
S4, setting a time threshold according to the vein phase, and screening out an artery candidate region according to the time threshold;
the step S4 specifically includes: and acquiring the peak time of the vein point as a time threshold, and filtering all the time threshold and the subsequent areas to obtain the artery candidate area.
The time threshold is taken to be the first 2s of the venous phase time.
Step S4 is specifically realized by the following steps:
s41, obtaining an artery registration map, namely a brain blood vessel region map containing clinical standards of artery registration regions, wherein the artery registration regions comprise a middle artery registration region and an anterior artery registration region;
s42, comparing the artery registration map, and screening out the middle artery and the anterior artery areas from the artery candidate areas as artery areas.
S5, carrying out space position constraint of registration on the artery candidate region to obtain an artery region;
and S6, extracting the brightest point in the artery area as an artery point, and calculating an artery curve.
When the arterial curve is calculated, the area near the brightest point in the arterial area is taken to be weighted average calculated, so that the arterial curve is obtained.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. A method for extracting arteriovenous points based on a CTP image is characterized by comprising the following steps: the method comprises the following steps:
s1, obtaining a blood vessel region image;
s2, screening out a vein region by using a 1/4 region under a brain region;
s3, extracting the brightest point in the vein area as a vein point, and calculating a vein curve;
s4, setting a time threshold according to the vein phase, and screening out an artery candidate region according to the time threshold;
s5, carrying out space position constraint of registration on the artery candidate region to obtain an artery region;
and S6, extracting the brightest point in the artery area as an artery point, and calculating an artery curve.
2. The CTP-image-based arteriovenous point extraction method of claim 1, wherein: the step S2 is specifically realized by the following steps:
s21, selecting a region with the time sequence change rate of 20-40 and the CT value higher than 150-200Hu in the blood vessel region image as a vein candidate region;
s22, acquiring a time series ID corresponding to the maximum CT value of the vein candidate region;
s23, screening out images which are larger than or equal to the time series ID and contain the vein candidate region, and filtering out the region corresponding to the 1/4 region under the brain region in the images to obtain the vein region.
3. The CTP-image-based arteriovenous point extraction method of claim 2, wherein: and when the vein curve is calculated, the weighted average calculation is carried out on the area near the brightest point in the vein area, so that the vein curve is obtained.
4. The CTP-image-based arteriovenous point extraction method of claim 3, wherein: the step S4 specifically includes: and acquiring the peak time of the vein point as a time threshold, and filtering all the time threshold and the subsequent areas to obtain the artery candidate area.
5. The CTP-image-based arteriovenous point extraction method of claim 4, wherein: the time threshold is taken to be the first 2s of the venous phase time.
6. The CTP-image-based arteriovenous point extraction method of claim 4, wherein: step S4 is specifically realized by the following steps:
s41, obtaining an artery registration map, namely a brain blood vessel region map containing clinical standards of artery registration regions, wherein the artery registration regions comprise a middle artery registration region and an anterior artery registration region;
s42, comparing the artery registration map, and screening out the middle artery and the anterior artery areas from the artery candidate areas as artery areas.
7. The CTP-image-based arteriovenous point extraction method of claim 6, wherein: when the arterial curve is calculated, the area near the brightest point in the arterial area is taken to be weighted average calculated, so that the arterial curve is obtained.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114511670A (en) * | 2021-12-31 | 2022-05-17 | 深圳市铱硙医疗科技有限公司 | Blood vessel reconstruction method, device, equipment and medium based on dynamic perfusion image |
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| US20050033159A1 (en) * | 2000-03-30 | 2005-02-10 | Mistretta Charles A. | Magnetic resonance angiography with automated vessel segmentation |
| CN109431532A (en) * | 2018-12-25 | 2019-03-08 | 上海联影医疗科技有限公司 | Artery and vena separation method and device and computer installation based on Perfusion Imaging |
| CN111105404A (en) * | 2019-12-24 | 2020-05-05 | 强联智创（北京）科技有限公司 | Method and system for extracting target position based on brain image data |
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