CN111354004B - Left and right ear region segmentation method based on temporal bone CT flat scan image - Google Patents
Left and right ear region segmentation method based on temporal bone CT flat scan image Download PDFInfo
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Abstract
The invention belongs to the technical field of medical image processing, and particularly relates to a left and right ear region segmentation method based on a temporal bone CT flat scan image. The algorithm is used for segmenting the left and right ear regions in the head temporal bone CT image, so that the computer can intensively perform subsequent processing on the ear regions. The invention comprises the following steps in sequence: removing invalid regions of the head CT image; cutting out the left ear area and the right ear area in the image according to the proportion; and respectively sorting and storing the left ear area image and the right ear area image. Experimental results show that for the flat-scan temporal bone CT image, the method can eliminate invalid black areas, abandon information of other irrelevant parts and accurately extract left and right ear areas.
Description
Technical Field
The invention belongs to the technical field of medical image processing, and particularly relates to a left and right ear region segmentation method based on a temporal bone CT flat scan image.
Background
With the development of computer science, intelligent medical treatment becomes a great technological innovation for improving the modern medical treatment level. The advantages it has in various aspects are gaining increasing acceptance and attention. Among them, the medical image processing technology is one of the key parts for promoting the development of intelligent medical treatment, and is also a very important application link of intelligent medical treatment.
In the application scene of otology CT image diagnosis, doctors can only obtain a whole temporal bone CT image at the present stage, so as to diagnose the ear pathological changes of patients. However, when the doctor actually makes a diagnosis, only the ear region in the temporal bone CT image is observed and relied on. The area is very small, and the length and width of a single area are less than 1/5 of the whole picture. Other redundant CT information is redundant without assistance for otology diagnosis. Not only doctors, but also otology image processing algorithms, redundant non-ear information is useless for the operation and judgment of ear information, and sometimes even serious interference is generated. Therefore, a program or an algorithm is needed to process the temporal bone CT image and extract the left and right ear regions.
So far, no special algorithm is used for segmenting and extracting left and right ear regions of a temporal bone CT image.
Disclosure of Invention
In order to fill up the blank of related algorithms, the invention provides a left and right ear region segmentation method based on a temporal bone CT flat scan image.
The invention provides a left and right ear region segmentation method based on a temporal bone CT flat scan image.
(1) Cropping and size normalization of active areas
Suppose an input temporal bone CT medical image I of size H0×W0(ii) a Wherein the gray value of each pixel has a value range of [0,65535](ii) a The method adopts T as a threshold value binarization input image to obtain a mapping Map, so that an effective area is 1, an invalid black area is 0, and a formula is recorded as follows:
wherein, the range of the T can be taken as [400,550], and the value is suggested to be 500 according to the value range of the pixel gray value and the gray value distribution of the effective area; and then, carrying out transverse and longitudinal summation on the Map to obtain MapX and MapY, wherein the formula is recorded as:
using MapY meterCalculating an upper boundary UP and a lower boundary DOWN of the effective region; UP being greater than threshold T in vector MapY1And DOWN is the index of the first element of the vector MapY above the threshold T1Subscript of the last element of (a); wherein, T1The value is 10, namely, when the number of the effective pixels in the horizontal direction reaches more than 10, the effective pixels are regarded as the boundary; in the same way, MapX is used to find the LEFT boundary LEFT and the RIGHT boundary RIGHT of the effective area, where the threshold is also T1;
Cutting I into I', and expressing the formula as follows:
I′={I(x,y)|LEFT≤x≤RIGHT,UP≤y≤DOWN} (4)
finally, unifying the size of I' to H by using a Bicubic interpolation method1×W1(ii) a Here H1、W1May be different from the original size H0、W0The same may be true; for simple operation, uniform and moderate input size, H1、W1A suggested value is 512.
(2) Cropping of left and right ear regions and discarding of extraneous regions
In the normalized effective region CT image I', the Area of the left ear is croppedlArea of right earrThe method comprises the following steps:
Areal={I′(x,y)|leftl≤x≤rightl,up≤y≤down} (5)
Arear={I′(x,y)|leftr≤x≤rightr,up≤y≤down} (6)
left of the above typel,rightlUp, down are boundary variables of the left and right ear regions; wherein, according to the characteristics of the CT flat scanning image of the temporal bone, leftlThe value range is [260,265 ]],rightlThe value range is [510,512 ]],leftrThe value range is [1,5 ]],rightrThe value range is [245,255 ]]And up has a value range of [195,205 ]]The down value range is [325,335 ]]。
(3) Classification and arrangement of left and right ear regions
For temporal bone CT medical image set to be processedTake picture I thereinjRepeating the steps (2) and (3), and combining the final results to form a final left ear CT area setAnd right ear CT region setThe formula is expressed as:
the invention has the beneficial effects that: the left and right ear images are clearly and completely extracted from the whole temporal bone CT image, the operation speed is high, and the method is simple and effective. Under the application scene of otology disease diagnosis, the independent left and right ear CT images can better serve doctors or intelligent medical systems, effective information is provided, and the interference of redundant information is avoided.
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FIG. 1 is a flow chart of the present invention.
Figure 2 is a demonstration of the results using the present invention.
Detailed Description
For an input temporal bone CT picture I, the left and right ear areas are segmented and extracted. The method comprises the following specific steps:
(1) and (5) carrying out binarization on the effective region of the I by using a threshold value T of 500 to obtain a binarized feature map. And calculating an upper boundary UP, a lower boundary DOWN, a LEFT boundary LEFT and a RIGHT boundary RIGHT of the effective region according to the feature map. Cutting the I according to the boundary, and utilizing Bicubic algorithm interpolation to enlarge the cut effective area CT image to 512 multiplied by 512;
(2) cropping of left and right ear regions is associated with discarding of extraneous regions.The range of the right ear region is: upper boundary up of 200, lower boundary down of 300, left boundary leftrGet 1, right margin rightrTaking 250; the range of the left ear region is: upper boundary up of 200, lower boundary down of 300, left boundary leftlGet 263, right border rightlAnd taking 512. According to the range, cutting the two regions in the CT image of the effective region to obtain the left and right ear regions of a single picture;
(3) and (5) classifying and sorting the left ear region and the right ear region. The left ear and right ear regions of all pictures are repeatedly calculated and divided, and the results are merged to finally form a left ear CT image set and a right ear CT image set.
FIG. 2 is a graph showing the results of the present invention. It can be seen that the invention can correctly segment the left and right ear regions from the entire temporal bone CT.
Claims (7)
1. A left and right ear region segmentation method based on a temporal bone CT flat scan image is characterized by comprising the following specific steps:
(1) cropping and size normalization of active areas
Suppose an input temporal bone CT medical image I of size H0×W0The gray value of the pixel is in the range of [0,65535]And adopting T as a threshold value binarization input Map to obtain a Map, so that the effective area is 1, the invalid black area is 0, and the formula is recorded as follows:
and summing the Map longitudinally and transversely to obtain MapX and MapY, wherein the formula is recorded as:
the upper bound UP of the active area is calculated using MapY, the lower bound DOWN, UP being greater than a threshold T in the vector MapY1And DOWN is the index of the first element of the vector MapY above the threshold T1Subscript of the last element of (a); similarly, the LEFT boundary LEFT and the RIGHT boundary RIGHT of the effective area are respectively obtained by using MapX;
cutting I into I', and expressing the formula as follows:
I′={I(x,y)|LEFT≤x≤RIGHT,UP≤y≤DOWN} (4)
finally, unifying the size of I' to H by using a Bicubic interpolation method1×W1;
(2) Cropping of left and right ear regions and discarding of extraneous regions
In the normalized effective region CT image I', the Area of the left ear is croppedlArea of right earrThe following were used:
Areal={I′(x,y)|leftl≤x≤rightl,up≤y≤down} (5)
Arear={I′(x,y)|leftr≤x≤rightr,up≤y≤down} (6)
wherein leftl,rightlUp, down are boundary variables of the left and right ear regions;
(3) classification and arrangement of left and right ear regions
For temporal bone CT medical image set to be processedWherein N is the number of elements in the CT image set; take picture I thereinjRepeating the steps (1), (2) and (3), and combining the final results to form a final left ear CT area setAnd right ear CT region setIs expressed as:
2. The method as claimed in claim 1, wherein in step (1), the threshold value T is 400-550.
3. The method of claim 1, wherein in step (1), the threshold T is set1Is 10.
4. The method according to claim 1, wherein in step (1), H is1、W1Value of and H0、W0The same is true.
5. The method of claim 1, wherein in step (2), leftlThe value is 260-lThe values are 510 and 512.
6. The method of claim 1, wherein in step (2), leftrThe value is 1-5, rightrThe value is 245-255.
7. The method as claimed in claim 1, wherein in step (2), the up value is 195-.
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CN102096900A (en) * | 2007-08-30 | 2011-06-15 | 精工爱普生株式会社 | Image processing device, image processing method, and image processing program |
EP2840551A1 (en) * | 2013-08-23 | 2015-02-25 | Vistaprint Schweiz GmbH | Methods and systems for automated selection of regions of an image for secondary finishing and generation of mask image of same |
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