CN101390753A - CT thin-layer ultrahigh resolution image density conversion method - Google Patents
CT thin-layer ultrahigh resolution image density conversion method Download PDFInfo
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- CN101390753A CN101390753A CNA2008102016704A CN200810201670A CN101390753A CN 101390753 A CN101390753 A CN 101390753A CN A2008102016704 A CNA2008102016704 A CN A2008102016704A CN 200810201670 A CN200810201670 A CN 200810201670A CN 101390753 A CN101390753 A CN 101390753A
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Abstract
Disclosed is a thin ultrahigh-resolution CT image density conversion method, including the following steps: acquiring an ultrahigh-resolution CT image through CT scanning; calculating the corresponding maximum density value of each pixel of the CT image; converting the maximum density value of each pixel of the CT image into a square column, and saving the converted image; wherein the length of the square column corresponds with the maximum density value of the pixel. Through density-image conversion of the ultrahigh-resolution CT image, the density conversion method converts the density value of the scanned image into a three-dimensional picture, so the density characteristic of a focus tissue can be observed from each layer and the three-dimensional structure of the scanned object, thus making the image looking clearer and more visual.
Description
Technical field
The present invention relates to a kind of image density conversion method, relate in particular to a kind of CT thin-layer ultrahigh resolution image density conversion method.
Background technology
CT is a kind of multiple functional state of an illness detection instrument, it is that electronic computer x-ray tomography scanning technique is called for short, the working procedure of CT is such: it is according to human body different tissues different to the absorption of X line and transmitance, using the high instrument of sensitivity measures human body, to measure the data input electronic computer that is obtained then, after electronic computer is handled data, just can photograph section or spatial image that human body is examined the position, find the tiny pathological changes at any position in the body.
CT scans the certain thickness aspect of human body portion with the X wire harness, receive the X line of this aspect of seeing through by detector, after changing visible light into, become the signal of telecommunication by opto-electronic conversion, transfer digital signal to through analog/digital converter (analog/digital converter) again, the input Computer Processing.The processing that a kind of image forms is with just like selected aspect is divided into the identical cuboid of several volumes, is referred to as voxel (voxe1).Scanning gained information obtains the X line attenuation coefficient or the absorptance of each voxel as calculated, is arranged in matrix again, i.e. character matrix (digital matrix), and character matrix can be stored in disk or the CD.Through digital/analog converter (digital/analog converter) each numeral in the character matrix is transferred to by black to the blockage that does not wait gray scale in vain, be pixel (pixel), and press matrix and arrange, promptly constitute the CT image, so, the CT image is a reconstructed image, the X linear absorption coefficient of each voxel can be calculated by different mathematical methods, and the CT image is again a layer images, and commonly used is the transverse section, in order to show whole organ, need a plurality of successive layer images.
At present, small pulmonary nodules CT Differential Diagnosis is a difficult problem that often faces in the daily curative activity of radiologist, existing lung tumors imaging diagnosis is the image of taking according to the CT image-forming principle, the conclusion of inferring according to the performance of lesion image form and anatomical relationship and doctor's diagnosis experience in the past.Not high with the pathology dependency of tumor.The conventional lung scanning parameter of CT that now is used for thoracic diagnosis is 512 squares of matrixes, bed thickness 5mm, scan vision 50cm, the spatial resolution of primary signal and density resolution are all inadequate for pulmonary's small lesion, the CT image of Xian Shiing can only once show 256 grades of gray scales simultaneously, existing scanning technique can't break through this restriction, can't see simultaneously that the tumor focus global density distributes and form, causes the tumor focus quality of image not high.
Summary of the invention
Low at the CT image resolution ratio that exists in the prior art, as to be difficult for observation problem, the present invention proposes a kind of scanning accuracy height and can observe the image conversion method at CT scan position from Density Distribution, three dimensional structure.
For solving the problems of the technologies described above, the invention provides a kind of CT thin-layer ultrahigh resolution image density conversion method, may further comprise the steps:
S1: obtain a ultrahigh resolution CT image by CT scan;
S2: calculate the pairing maximum density values of each pixel in the described CT image;
S3: convert the maximum density values of each pixel in the described CT image to a square column, the length of described square column is preserved the image after changing corresponding to the maximum density values of described pixel.
Optionally, the bed thickness of described CT scan is less than or equal to 1 millimeter.
Optionally, the scan vision of described CT scan is less than 18 centimetres.
Optionally, the pixel of described CT image is the matrix of 1024*1024.
The present invention provides a kind of CT thin-layer ultrahigh resolution image density conversion method in addition, may further comprise the steps:
A1: obtain a ultrahigh resolution CT image by CT scan;
A2: calculate the pairing maximum density values of each pixel in the described CT image;
A3: the density addition with each pixel at all corresponding positions of described CT image forms a new CT image;
A4: convert the maximum density values of each pixel in the described new CT image to a square column, the length of described square column is corresponding to the maximum density values of described pixel.
Optionally, the bed thickness of described CT scan is less than or equal to 1 millimeter.
Optionally, the scan vision of described CT scan is less than 18 centimetres.
Optionally, the pixel of described CT image is the matrix of 1024*1024.
The beneficial effect of CT thin-layer ultrahigh resolution image density conversion method of the present invention is: selected the higher CT scan image of pixel for use, pass through image transitions, convert scintigram to axonometric chart, can observe from scanned every layer of structure and three dimensional structure, thereby make image seem more clear, more directly perceived.
Description of drawings
Fig. 1 is the flow chart of CT thin-layer ultrahigh resolution image density conversion method first embodiment of the present invention;
Fig. 2 is the flow chart of CT thin-layer ultrahigh resolution image density conversion method second embodiment of the present invention;
Fig. 3 is the three-dimensional CT image of CT thin-layer ultrahigh resolution image density conversion method first embodiment of the present invention.
The specific embodiment
Below in conjunction with caption preferred embodiment of the present invention.
At first please refer to Fig. 1 and Fig. 3, Fig. 1 is the flow chart of CT thin-layer ultrahigh resolution image density conversion method first embodiment of the present invention, Fig. 3 is the three-dimensional CT image of CT thin-layer ultrahigh resolution image density conversion method first embodiment of the present invention, as can be seen from Figure 1, the method comprising the steps of 110: obtain a ultrahigh resolution CT image by CT scan; Step 111: calculate the pairing maximum density values of each pixel in the described CT image; Step 112: convert the maximum density values of each pixel in the described CT image to a square column, the length of described square column is preserved the image after changing corresponding to the maximum density values of described pixel.The bed thickness of described CT scan is 1 millimeter, the scan vision of described CT scan is less than 18 centimetres, the pixel of described CT image is the matrix of 1024*1024, adopt above condition to carry out the CT scan tumor and can accomplish that the spatial resolution of each pixel reaches below the 0.06mm, the volume effect of density resolution also reduces to 1mm, and by above conversion, just can be from by on the molecular three-dimensional CT image of square column, be to see complete Density Distribution information on Fig. 3, simultaneously can be by the X in the software operation rotation diagram 3, Y-axis, just can see the distribution of the density value of all angles, when having generated three-dimensional CT image, the grey level histogram that is produced by this width of cloth CT image passes through to regulate the width of minimax density, the density indication range of selecting to change stereo-picture can be arranged,, react the Density Distribution of certain one deck tumor by to conversion and demonstration with last layer CT image.
Then please refer to Fig. 2, Fig. 2 is the flow chart of CT thin-layer ultrahigh resolution image density conversion method second embodiment of the present invention, as can be seen from the figure, comprises step 210: obtain a ultrahigh resolution CT image by CT scan; Step 211: calculate the pairing maximum density values of each pixel in the described CT image; Step 212: the density addition with each pixel at all corresponding positions of described CT image forms a new CT image; Step 213: convert the maximum density values of each pixel in the described new CT image to a square column, the length of described square column is corresponding to the maximum density values of described pixel, the scan vision of described CT scan is less than 18 centimetres, the pixel of described CT image is the matrix of 1024*1024, adopt above condition to carry out the CT scan tumor and can accomplish that the spatial resolution of each pixel reaches below the 0.06mm, the volume effect of density resolution also reduces to 1mm, and by above conversion, just obtain the multi-Slice CT image axonometric chart that a width of cloth is made up of pillar in many ways, can carry out whole observation from the three dimensional structure that is scanned the position.
Though the present invention discloses as above with preferred embodiment, so it is not in order to limit the present invention.The persond having ordinary knowledge in the technical field of the present invention, without departing from the spirit and scope of the present invention, when being used for a variety of modifications and variations.Therefore, protection scope of the present invention is as the criterion when looking claims person of defining.
Claims (8)
1. CT thin-layer ultrahigh resolution image density conversion method is characterized in that may further comprise the steps:
S1: obtain a ultrahigh resolution CT image by CT scan;
S2: calculate the pairing maximum density values of each pixel in the described CT image;
S3: convert the maximum density values of each pixel in the described CT image to a square column, the length of described square column is preserved the image after changing corresponding to the maximum density values of described pixel.
2. according to the described CT thin-layer ultrahigh resolution image density conversion method of claim 1, the bed thickness that it is characterized in that described CT scan is smaller or equal to 1 millimeter.
3. according to the described CT thin-layer ultrahigh resolution image density conversion method of claim 1, the scan vision that it is characterized in that described CT scan is smaller or equal to 18 centimetres.
4. according to the described CT thin-layer ultrahigh resolution image density conversion method of claim 1, the pixel that it is characterized in that described CT image is the matrix of 1024*1024.
5. CT thin-layer ultrahigh resolution image density conversion method is characterized in that may further comprise the steps:
A1: obtain a ultrahigh resolution CT image by CT scan;
A2: calculate the pairing maximum density values of each pixel in the described CT image;
A3: the density addition with each pixel at all corresponding positions of described CT image forms a new CT image;
A4: convert the maximum density values of each pixel in the described new CT image to a square column, the length of described square column is corresponding to the maximum density values of described pixel.
6. according to the described CT thin-layer ultrahigh resolution image density conversion method of claim 5, the bed thickness that it is characterized in that described CT scan is smaller or equal to 1 millimeter.
7. according to the described CT thin-layer ultrahigh resolution image density conversion method of claim 5, the scan vision that it is characterized in that described CT scan is less than 18 centimetres.
8. according to the described CT thin-layer ultrahigh resolution image density conversion method of claim 5, the pixel that it is characterized in that described CT image is the matrix of 1024*1024.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108121942A (en) * | 2016-11-30 | 2018-06-05 | 南昌欧菲生物识别技术有限公司 | A kind of method and device of fingerprint recognition |
| CN108362716A (en) * | 2018-03-22 | 2018-08-03 | 四川大学 | A kind of historical relic material detection determination method and detection device based on Medical CT |
| CN110349115A (en) * | 2019-07-04 | 2019-10-18 | 邃蓝智能科技(上海)有限公司 | CT image processing system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4505805B2 (en) * | 2004-08-02 | 2010-07-21 | 横河電機株式会社 | Region extraction method and apparatus |
| US7705314B2 (en) * | 2006-06-06 | 2010-04-27 | General Electric Company | Method and apparatus for PET time of flight generation of compression sinogram and image reconstruction |
| CN100470587C (en) * | 2007-01-26 | 2009-03-18 | 清华大学 | Method for segmenting abdominal organ in medical image |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108121942A (en) * | 2016-11-30 | 2018-06-05 | 南昌欧菲生物识别技术有限公司 | A kind of method and device of fingerprint recognition |
| CN108362716A (en) * | 2018-03-22 | 2018-08-03 | 四川大学 | A kind of historical relic material detection determination method and detection device based on Medical CT |
| CN110349115A (en) * | 2019-07-04 | 2019-10-18 | 邃蓝智能科技(上海)有限公司 | CT image processing system |
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