CN112419395A - Method for determining collapse temperature of freeze-dried material by using image processing technology - Google Patents
Method for determining collapse temperature of freeze-dried material by using image processing technology Download PDFInfo
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- CN112419395A CN112419395A CN202011331620.5A CN202011331620A CN112419395A CN 112419395 A CN112419395 A CN 112419395A CN 202011331620 A CN202011331620 A CN 202011331620A CN 112419395 A CN112419395 A CN 112419395A
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- 238000000034 method Methods 0.000 title claims abstract description 51
- 239000000463 material Substances 0.000 title claims abstract description 39
- 238000004108 freeze drying Methods 0.000 claims abstract description 37
- 230000008569 process Effects 0.000 claims abstract description 13
- 238000001914 filtration Methods 0.000 claims abstract description 9
- 238000001035 drying Methods 0.000 claims description 14
- 239000006059 cover glass Substances 0.000 claims description 3
- 230000000630 rising effect Effects 0.000 abstract 1
- 238000002474 experimental method Methods 0.000 description 10
- 239000011159 matrix material Substances 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 239000007787 solid Substances 0.000 description 3
- 239000013078 crystal Substances 0.000 description 2
- 230000004069 differentiation Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003169 placental effect Effects 0.000 description 2
- 238000000859 sublimation Methods 0.000 description 2
- 230000008022 sublimation Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 210000003850 cellular structure Anatomy 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 230000000007 visual effect 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
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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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
- G06T5/40—Image enhancement or restoration using histogram techniques
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- G—PHYSICS
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- 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
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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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
- G06T2207/10004—Still image; Photographic image
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- Drying Of Solid Materials (AREA)
Abstract
The invention discloses a method for determining the collapse temperature of a freeze-dried material by utilizing an image processing technology, which comprises the following steps of: s1, obtaining an image of the freeze-dried material in the temperature rising process through a freeze-drying microscope; s2, converting the gray level image into a binary image according to a proper threshold value T by selecting the image number obtained by the freeze-drying microscope; s3, judging whether the threshold T in the step S2 is reasonable, returning to the step S2 when the judgment is unreasonable, and carrying out the next step when the judgment is reasonable; s4, cutting the black edge information at the lower part of the image obtained in the step S2; s5, cutting the image obtained in the step S4; s6, operating an area filtering program; s7, judging whether the area filtering value in the step S6 is reasonable or not; s8, filtering the points with smaller area in the image obtained in the step S6. According to the invention, the accurate collapse temperature data with good stability is obtained through the image processing technology, and the data error caused by subjective idea is avoided.
Description
Technical Field
The invention relates to the technical field of determining the collapse temperature of a freeze-dried material, in particular to a method for determining the collapse temperature of the freeze-dried material by using an image processing technology.
Background
Freeze-drying is a widely used method for preserving biological products. During freeze-drying, when the temperature of the drying layer rises to a certain value, the ice crystals in the material disappear, and the space originally occupied by the ice crystals becomes a cavity, so that the freeze-drying layer is in a porous honeycomb sponge structure. This structure is temperature dependent. When the solid matrix temperature of the honeycomb structure is higher, the rigidity thereof is lowered. When the temperature reaches a critical temperature, called the collapse temperature of the freeze-dried material, the solid matrix is not rigid enough to maintain the cellular structure, the walls of the solid matrix of the cavities collapse, and the channels for the original vapor diffusion are closed. When the critical temperature of primary drying is higher than the collapse temperature, the loss of the porous structure of the drying layer, the increase of residual moisture and the prolonging of rehydration time can be caused, and the loss of the activity of the biological product can be caused more seriously. Therefore, the collapse temperature is a very important parameter in the freeze-drying process, and has guiding significance for the freeze-drying of the material. Therefore, the collapse temperature is used as the critical temperature, and the primary drying critical temperature of the material is set below the collapse temperature, so that the sublimation drying rate can be improved, and the freeze-drying time can be shortened. At present, the collapse temperature of a freeze-dried material is determined by simulating a cooling process by using a freeze-drying microscope, then, an image set acquired by the freeze-drying microscope is observed by visual observation, when the material is close to a sublimation interface in a drying area and has a cavity, the material can be considered to be collapsed, an experiment is repeated for many times, and the average value of temperature points is the collapse temperature. However, the method has strong subjectivity, and the experimental result may be fuzzy after the experiment is repeated for many times, so that the experimental result is inaccurate. After the freeze drying is applied to actual freeze drying, the quality of the product is reduced.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method for determining the collapse temperature of a freeze-dried material by using an image processing technology, and the area change rate of a drying area is calculated by using the image processing technology, so that accurate collapse temperature data with good stability is obtained, and data errors caused by subjective ideas are avoided. To achieve the above objects and other advantages in accordance with the present invention, there is provided a method for determining a collapse temperature of a lyophilized material using image processing techniques, comprising the steps of:
s1, acquiring images, and obtaining images of the freeze-dried materials in the temperature rise process through a freeze-drying microscope;
s2, converting the gray level image into a binary image according to a proper threshold value T by selecting the image number obtained by the freeze-drying microscope;
s3, judging whether the threshold T in the step S2 is reasonable, if the threshold T is unreasonable, returning to the step S2 again, and if the threshold T is reasonable, performing the next step;
s4, cutting the black edge information at the lower part of the image obtained in the step S2;
s5, cutting the image obtained in the step S4;
s6, operating an area filtering program;
s7, judging whether the area filter value in the step S6 is reasonable, returning to the step S6 when the judgment is unreasonable, and carrying out the next step when the judgment is reasonable;
s8, filtering the points with smaller area in the image obtained in the step S6;
s9, calculating the area ratio of each temperature point in the image obtained in the step S8;
and S10, differentiating the area ratio data at all the temperature points by using software to obtain a curve.
Preferably, the step S1 further includes:
s11, placing a proper amount of material in the center of an objective table of a freeze-drying microscope, and covering a cover glass;
and S12, adjusting the magnification of the freeze-drying microscope, screwing the cover of the freeze-drying microscope, setting a freeze-drying program, and starting the freeze-drying microscope to obtain an image set in the temperature rise process.
Preferably, the step S2 further includes dividing the data of the image into two parts by T, where the two parts include pixel groups larger than T and pixel groups smaller than T.
Preferably, the step S4 includes a data set with clipped pixels 2048 × 1536.
Preferably, in the step S6, the horizontal coordinate size of the leftmost point of the drying line is cut as the length of the cut picture.
Compared with the prior art, the invention has the beneficial effects that: an image set of the material in the temperature rise process is acquired by using a freeze-drying microscope, then binarization processing is carried out on the image set, and after the steps of cutting, area filtering and the like, the area change rate of a dry area is calculated, so that accurate collapse temperature data with good stability is obtained.
Drawings
FIG. 1 is a block flow diagram of a method for determining the collapse temperature of a lyophilized material using image processing techniques in accordance with the present invention;
FIG. 2 is a graph showing the experimental results of the first collapse temperature at a temperature increase rate of 2 deg.C/min in the method for determining the collapse temperature of a lyophilized material using image processing techniques according to the present invention;
FIG. 3 is a graph showing the experimental results of the second collapse temperature at a temperature increase rate of 2 deg.C/min for the method of determining the collapse temperature of a lyophilized material using image processing techniques according to the present invention;
FIG. 4 is a graph showing the third collapse temperature experiment result when the temperature increase rate is 2 deg.C/min according to the method for determining the collapse temperature of the freeze-dried material by using the image processing technique of the present invention;
FIG. 5 is a graph of a freeze drying microscope during temperature ramp-up for a method of determining the collapse temperature of a freeze dried material using image processing techniques in accordance with the present invention;
FIG. 6 is a binarized image of a method for determining the collapse temperature of a freeze-dried material using image processing techniques according to the present invention;
FIG. 7 is a diagram of a black-edged trim of a method for determining the collapse temperature of a freeze-dried material using image processing techniques according to the invention;
FIG. 8 is a diagram of a regional cropping of a method for determining the collapse temperature of a lyophilized material using image processing techniques according to the present invention;
figure 9 is a graph of the area filtering of a method for determining the collapse temperature of a lyophilised material using image processing techniques according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-9, a method for determining the collapse temperature of a lyophilized material using image processing techniques, comprising the steps of: s1, acquiring images, and obtaining images of the freeze-dried materials in the temperature rise process through a freeze-drying microscope;
s2, numbering the images obtained by the freeze-drying microscope, and converting the gray level images into binary images according to a proper threshold value T by selecting the threshold value T;
s3, judging whether the threshold T in the step S2 is reasonable, if the threshold T is unreasonable, returning to the step S2 again, and if the threshold T is reasonable, performing the next step;
s4, cutting the black edge information at the lower part of the image obtained in the step S2;
s5, cutting the image obtained in the step S4;
s6, operating an area filtering program;
s7, judging whether the area filter value in the step S6 is reasonable, returning to the step S6 when the judgment is unreasonable, and carrying out the next step when the judgment is reasonable;
s8, filtering the points with smaller area in the image obtained in the step S6;
s9, calculating the area ratio of each temperature point in the image obtained in the step S8;
and S10, differentiating the area ratio data at all the temperature points by using software to obtain a curve.
Further, the step S1 further includes:
s11, placing a proper amount of material in the center of an objective table of a freeze-drying microscope, and covering a cover glass;
and S12, adjusting the magnification of the freeze-drying microscope, screwing the cover of the freeze-drying microscope, setting a freeze-drying program, and starting the freeze-drying microscope to obtain an image set in the temperature rise process.
Further, the step S2 includes dividing the data of the image into two parts by T, where the two parts include pixel groups larger than T and pixel groups smaller than T.
Further, the step S4 includes a data set with clipped pixels 2048 × 1536.
Further, the horizontal coordinate size of the leftmost point of the drying line is cut in the step S6 as the length of the cut picture.
An example is the collapse temperature of 5% placental decellularized matrix determined using image processing when the temperature ramp rate is 2 ℃/min, as follows:
(1) experimental procedures
a. Collecting an image: 6 microliters of 5% placental acellular matrix was placed in the center of the stage of the lyophilization microscope and covered with a cover slip. The cover of the freeze-drying microscope was screwed down and the magnification was adjusted to 20 times. Setting a freeze-drying program, namely reducing the temperature from room temperature to-30 ℃ at a speed of 10 ℃/min, and keeping the temperature constant for 7 minutes. Then the temperature is raised to-15 ℃ at the speed of 2 ℃/min. Starting the freeze-drying microscope to obtain an image set in the process of temperature rise.
b. Binarization: the image obtained by the freeze-drying microscope is numbered, an appropriate threshold value T is selected, and the data of the image are divided into two parts (a pixel group larger than T and a pixel group smaller than T) by the T. And running a program, and converting the gray level image into a binary image according to the threshold value T.
c. Cutting a black edge: the lower part of the image collected by the freeze-drying microscope contains information such as temperature, temperature rate, time and the like. And c, cutting the black edge information at the lower part of the image obtained in the step b, and running a program to obtain a data set with pixels of 2048 × 1536.
d. Area cutting: as the temperature rises, the drying line will gradually move from left to right. When the collapse of the material occurs, the dried material in the drying zone becomes non-uniform. The collapse temperature is determined by utilizing the area change rate of the binarized image at each temperature point. The frozen area on the right side of the drying line therefore needs to be trimmed away. The specific method is that the horizontal coordinate size of the leftmost point of the drying line is used as the length of the picture after cutting. C, cutting the image obtained in the step c
e. Area filtering: and c, running a program, and filtering the points with smaller areas in the image obtained in the step d to remove errors possibly caused by density.
f. Calculating the area ratio: and e, running a program, and calculating the area ratio of each temperature point in the image obtained in the step e.
g. Analysis of the rate of change: and differentiating the area ratio data under all the temperature points by using Origin software to obtain a curve. The sudden temperature point can be identified as the collapse temperature of the material.
Repeating the experiment for three times, and taking the average value as the collapse temperature
(2) Analysis of results
TABLE area ratio of the first experiment at a heating rate of 2 deg.C/min
As in the differentiation process of fig. 2, the area ratios at which the collapse temperature point is determined are as follows:
second experiment area ratio with temperature rise rate of 2 ℃/min
As in the differentiation process of fig. 3, collapse temperature points were determined, and area ratios were as follows:
area ratio of third experiment when third temperature rise rate is 2 ℃/min
The collapse temperature point was determined by differentiating the process shown in FIG. 4, and the results obtained by repeating the experiment 3 times under the same conditions were as follows:
| number of experiments | Collapse temperature (. degree. C.) |
| For the first time | 23.3 |
| For the second time | 23.3 |
| The third time | 23.6 |
The method is adopted to judge the collapse temperature of the material, so that experimental errors caused by subjectivity are avoided. The result can be directly obtained through software analysis.
The number of devices and the scale of the processes described herein are intended to simplify the description of the invention, and applications, modifications and variations of the invention will be apparent to those skilled in the art.
While embodiments of the invention have been described above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in various fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein without departing from the general concept defined by the appended claims and their equivalents.
Claims (5)
1. A method for determining the collapse temperature of a freeze-dried material by using an image processing technology is characterized by comprising the following steps:
s1, acquiring images, and obtaining images of the freeze-dried materials in the temperature rise process through a freeze-drying microscope;
s2, numbering the images obtained by the freeze-drying microscope, and converting the gray level images into binary images according to a proper threshold value T by selecting the threshold value T;
s3, judging whether the threshold T in the step S2 is reasonable, if the threshold T is unreasonable, returning to the step S2 again, and if the threshold T is reasonable, performing the next step;
s4, cutting the black edge information at the lower part of the image obtained in the step S2;
s5, cutting the image obtained in the step S4;
s6, operating an area filtering program;
s7, judging whether the area filter value in the step S6 is reasonable, returning to the step S6 when the judgment is unreasonable, and carrying out the next step when the judgment is reasonable;
s8, filtering the points with smaller area in the image obtained in the step S6;
s9, calculating the area ratio of each temperature point in the image obtained in the step S8;
and S10, differentiating the area ratio data at all the temperature points by using software to obtain a curve.
2. The method for determining the collapse temperature of the lyophilized material using image processing technique as claimed in claim 1, wherein said step S1 further comprises:
s11, placing a proper amount of material in the center of an objective table of a freeze-drying microscope, and covering a cover glass;
and S12, adjusting the magnification of the freeze-drying microscope, screwing the cover of the freeze-drying microscope, setting a freeze-drying program, and starting the freeze-drying microscope to obtain an image set in the temperature rise process.
3. The method of claim 1, wherein the step S2 further comprises dividing the image data into two parts by T, wherein the two parts include pixels greater than T and pixels less than T.
4. The method of claim 1, wherein step S4 includes cropping the data set with 2048 x 1536 pixels.
5. The method for determining the collapse temperature of a lyophilized material using an image processing technique according to claim 1, wherein the cropping in step S6 is performed with the dimension of the abscissa of the leftmost point of the drying line as the length of the cropped picture.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006029467A1 (en) * | 2004-09-16 | 2006-03-23 | Btf Pty Ltd | Rapid freeze drying process |
| CN104931503A (en) * | 2015-07-08 | 2015-09-23 | 中国药科大学 | Freeze-drying microscope based on optical coherence tomography |
| CN111784668A (en) * | 2020-07-01 | 2020-10-16 | 武汉楚精灵医疗科技有限公司 | Digestive endoscopy image automatic freezing method based on perceptual hash algorithm |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006029467A1 (en) * | 2004-09-16 | 2006-03-23 | Btf Pty Ltd | Rapid freeze drying process |
| CN104931503A (en) * | 2015-07-08 | 2015-09-23 | 中国药科大学 | Freeze-drying microscope based on optical coherence tomography |
| CN111784668A (en) * | 2020-07-01 | 2020-10-16 | 武汉楚精灵医疗科技有限公司 | Digestive endoscopy image automatic freezing method based on perceptual hash algorithm |
Non-Patent Citations (1)
| Title |
|---|
| 郭树国 等: "基于图像处理优化真空冷冻干燥工艺参数", 《真空》 * |
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