CN113222837A - Automatic removing method of CT image scanning bed - Google Patents
Automatic removing method of CT image scanning bed Download PDFInfo
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- CN113222837A CN113222837A CN202110490362.3A CN202110490362A CN113222837A CN 113222837 A CN113222837 A CN 113222837A CN 202110490362 A CN202110490362 A CN 202110490362A CN 113222837 A CN113222837 A CN 113222837A
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- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000010606 normalization Methods 0.000 claims abstract description 7
- 238000002591 computed tomography Methods 0.000 abstract description 43
- 230000007797 corrosion Effects 0.000 abstract description 6
- 238000005260 corrosion Methods 0.000 abstract description 6
- 238000003759 clinical diagnosis Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000002595 magnetic resonance imaging Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000011218 segmentation Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 238000002059 diagnostic imaging Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000010339 dilation Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
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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
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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
- G06T7/155—Segmentation; Edge detection involving morphological operators
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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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Abstract
The invention discloses an automatic removing method of a CT image scanning bed, which comprises the steps of leading a CT image into image reading equipment, and searching the minimum value of all foreground pixels in the whole CT image; carrying out normalization processing; further binarization processing is carried out; creating a corresponding image mask; based on the obtained image mask, a volume mask is constructed, and when the background value of the volume mask is 0, the corresponding value of the volume mask in the original CT image is replaced by the minimum value. Compared with the prior art, the invention can automatically and quickly detect and remove the CT scanning bed. The invention is different from the CT bed-removing operation based on graphics (expansion, corrosion and the like), can sensitively judge the foreground and the background and successfully remove the CT scanning bed and the mattress thereof, wherein the mattress is not easy to position and remove by other methods.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to an automatic removing method of a CT image scanning bed.
Background
In recent years, medical imaging techniques have been rapidly developed, and Computed Tomography (CT), magnetic resonance imaging (MR), and the like are widely used in clinical diagnosis. The CT scanning bed is a tool for carrying a detected person to complete a scanning task, is provided with a vertical motion control system and a horizontal longitudinal motion control system, and can automatically enter and exit the aperture of a scanning frame according to the requirements of a program to complete the automatic positioning of the scanning position of a detected object. The CT scanning bed is always included in the CT image, which may interfere with the CT image and affect the accuracy of clinical diagnosis. The present document provides a novel automatic removal method for a CT image scanning bed by taking a human CT image as a specific study object.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an automatic removing method of a CT image scanning bed.
In order to achieve the purpose, the invention is implemented according to the following technical scheme:
an automatic removing method of a CT image scanning bed comprises the following steps:
s1, importing the CT image into image reading equipment, and searching the minimum value of all foreground pixels in the whole CT image;
s2, carrying out normalization processing based on the processing result of the step S1;
s3, further performing binarization processing based on the normalized CT image obtained in the step S2;
s4, creating a corresponding image mask based on the binarization processing result of the step S3;
s5, a volume mask is formed based on the image mask obtained in the above step S4, and when the background value of the volume mask is 0, its corresponding value in the original CT image is replaced with the minimum value.
Further, the step S2 specifically includes: normalization was performed in the range of [0,1] to obtain normalized CT volumes.
Further, the step S3 specifically includes: and carrying out binarization processing on the normalized CT volume by using the Otsu method, finding out the optimal threshold value of the foreground/background, and separating all objects from the background.
Further, the step S4 specifically includes:
s41, based on the processing result of the third step, finding out the contour lines of all objects in each axial CT image;
s42, based on the step S41, selecting the longest contour line containing the image center, and removing other contour lines;
s43, creating a corresponding image mask by using the foreground value 1 in the contour line selected in the step S42.
Compared with the prior art, the invention can automatically and quickly detect and remove the CT scanning bed. The invention is different from the CT bed-removing operation based on graphics (expansion, corrosion and the like), can sensitively judge the foreground and the background and successfully remove the CT scanning bed and the mattress thereof, wherein the mattress is not easy to position and remove by other methods.
Drawings
Fig. 1 is a schematic flow chart of an automatic removing method of a CT image scanning bed according to the present invention.
Fig. 2 is a diagram of an experimental result of the automatic removing method of the CT image scanning bed of the present invention, wherein: (a) for the original CT image, a CT scanning bed under the body of the patient can be seen; (b) the image is processed by binaryzation; (c) an image mask; (d) is a CT image after bed removal.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. The specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating an automatic removing method for a CT image scanning bed according to the present invention, which includes the following steps:
s1, importing the CT image into image reading equipment, and searching the minimum value of all foreground pixels in the whole CT image;
s2, normalization processing is performed based on the processing result of the step S1:
carrying out normalization processing in the range of [0,1] to obtain a normalized CT volume;
s3, further binarization processing based on the normalized CT image obtained in the above step S2:
carrying out binarization processing on the normalized CT volume by using an Otsu method, finding out the optimal threshold value of the foreground/background, and separating all objects from the background; in this embodiment, the ohd method is that Ohd (OTSU) threshold segmentation divides an image into a background and an object according to the gray characteristics of the image. The larger the inter-class variance between the background and the object, the larger the difference between the two parts constituting the image, and the smaller the difference between the two parts when part of the object is mistaken for the background or part of the background is mistaken for the object. Thus, a segmentation that maximizes the inter-class variance means that the probability of false positives is minimized. Morphology is mainly to obtain object topology and structure information, and to obtain more essential morphology of an object through some operations of interaction of the object and structural elements. The applications in image processing are mainly: the basic operation of morphology is utilized to observe and process the image, thereby achieving the purpose of improving the image quality. And corrosion and expansion in image morphology can well perform noise reduction treatment on the binary image. The specific operation of corrosion is: each pixel in the image is scanned with a structuring element (typically 3 x 3 in size), and each pixel in the structuring element is anded with its overlying pixel, which is 1 if both are 1, and 0 otherwise. The specific operation of the expansion is as follows: each pixel in the image is scanned with a structuring element (typically 3 x 3 in size), and each pixel in the structuring element is anded with its overlying pixel, if both are 0, then the pixel is 0, otherwise it is 1. The corrosion has the effects of eliminating boundary points of an object, reducing a target and eliminating noise points smaller than structural elements; the effect of the dilation is to incorporate all background points in contact with the object into the object, enlarging the object and filling in holes in the object. The start operation is a process of corrosion first and then expansion, and can eliminate fine noise on an image and smooth the boundary of an object.
S4, creating a corresponding image mask based on the binarization processing result of the step S3:
s41, based on the processing result of the third step, finding out the contour lines of all objects in each axial CT image;
s42, based on the step S41, selecting the longest contour line containing the image center, and removing other contour lines;
s43, creating a corresponding image mask by using the foreground value 1 in the contour line selected in the step S42;
s5, a volume mask is formed based on the image mask obtained in the above step S4, and when the background value of the volume mask is 0, its corresponding value in the original CT image is replaced with the minimum value.
Further, in order to verify the feasibility of the present invention, the CT scanning bed is removed by the above method, as shown in fig. 2, (a) in fig. 2 is the original CT image, and the CT scanning bed under the patient body can be seen; (b) the image is processed by binaryzation; (c) an image mask; after the above steps of the method are carried out, the CT image after bed removal in (d) is finally obtained, and the CT bed is completely removed from the CT image as can be seen from (d), thereby verifying the feasibility of the invention.
The technical solution of the present invention is not limited to the limitations of the above specific embodiments, and all technical modifications made according to the technical solution of the present invention fall within the protection scope of the present invention.
Claims (4)
1. An automatic removing method of a CT image scanning bed is characterized by comprising the following steps:
s1, importing the CT image into image reading equipment, and searching the minimum value of all foreground pixels in the whole CT image;
s2, carrying out normalization processing based on the processing result of the step S1;
s3, further performing binarization processing based on the normalized CT image obtained in the step S2;
s4, creating a corresponding image mask based on the binarization processing result of the step S3;
s5, a volume mask is formed based on the image mask obtained in the above step S4, and when the background value of the volume mask is 0, its corresponding value in the original CT image is replaced with the minimum value.
2. The method for automatically removing a CT image scanning bed as claimed in claim 1, wherein said step S2 specifically comprises: normalization was performed in the range of [0,1] to obtain normalized CT volumes.
3. The method for automatically removing a CT image scanning bed as claimed in claim 1, wherein said step S3 specifically comprises: and carrying out binarization processing on the normalized CT volume by using the Otsu method, finding out the optimal threshold value of the foreground/background, and separating all objects from the background.
4. The method for automatically removing a CT image scanning bed as claimed in claim 1, wherein said step S4 specifically comprises:
s41, based on the processing result of the third step, finding out the contour lines of all objects in each axial CT image;
s42, based on the step S41, selecting the longest contour line containing the image center, and removing other contour lines;
s43, creating a corresponding image mask by using the foreground value 1 in the contour line selected in the step S42.
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