Micro-Computed Tomography Soft Tissue Biological Specimens Image Data Visualization

: Visualization of soft tissues in microCT scanning using X-rays is still a complicated matter. There is no simple tool or methodology on how to set up an optimal look-up-table while respecting the type of soft tissue. A partial solution may be the use of a contrast agent. However, this must be accompanied by an appropriate look-up-table setting that respects the relationship between the soft tissue type and the Hounsﬁeld units. The main aim of the study is to determine experimentally derived look-up-tables and relevant values of the Hounsﬁeld units based on the statistical correlation analysis. These values were obtained from the liver and kidneys of 24 mice in solutions of ethanol as the centroid value of the opacity look-up-table area under this graph. Samples and phantom were scanned by a Bruker SkyScan 1275 micro-CT and Phywe XR 4.0 and processed using CTvox and ORS Dragonﬂy software. To reconstruct the micro-CT projections, NRecon software was used. The main ﬁnding of the study is that there is a statistically signiﬁcant relationship between the centroid of the area under the look-up-table curve and the number of days for which the animal sample was stored in an ethanol solution. H1 of the ﬁrst hypothesis, i.e. that suggested the Spearman’s correlation coefﬁcient does not equal zero (r 1 (cid:54) = 0) regarding this relationship was conﬁrmed. On the other hand, there is no statistically signiﬁcant relationship between the centroid of the area under the look-up-table curve and the concentration of the ethanol solution. In this case, H1 of the second hypothesis, i.e. that the Spearman’s correlation coefﬁcient does not equal zero (r 2 (cid:54) = 0) regarding this relationship was not conﬁrmed. Spearman’s correlation coefﬁcients were − 0.27 for the concentration and − 0.87 for the number of days stored in ethanol solution in the case of the livers of 13 mice and 0.06 for the concentration and 0.94 for the number of days stored in ethanol solution in the case of kidneys of 11 mice.


Introduction
Computed tomography (CT) imaging is widely used in medical practice, mainly due to the non-invasiveness of this method, its good spatial resolution, and the relatively short acquisition time of the required images. In addition to conventional CT, which is mainly used both for diagnostic and therapeutic procedures [1], high spatial resolution CT or micro-CT (µCT) are also used in practice [2]. These systems work on the same basic principle as the typical CT, except that the X-ray-tube-detector system does not perform rotational motion, but rotates the specimen. However, their advantage lies in their ability to scan samples with much higher spatial (<50 µm) and contrast resolution.
It is because of the non-destructiveness of this method in evaluating the scanned volume with high resolution that µCT devices are much used in both research and industry. Furthermore, even if the intrinsic noise of commercial µCT detectors is not a problem in many cases (especially in industry), the imaging of more delicate structures with a lower range of CT numbers (the same as Hounsfield units = HU), and the associated lower attenuation contrast between structures, such as soft tissues, is greatly hampered by this noise.
The present work, in collaboration with the Department of Anatomy at the 3rd Faculty of Medicine, Charles University (Prague, Czech Republic), is primarily focused on the visualization of soft tissues in particular, as well as the search for a methodology that could optimize the overall visualization process and make it easier. This also involves research and experimentation with new procedures and contrast agents to achieve the required contrast between soft tissues that is needed for visualization [3][4][5][6][7].
Two papers dealt with similar issues. The first one, i.e., [8], used an image histogram for optimal look-up-table (LUT) setup. Thus, it is not the same intention. The second work, i.e., [9], uses only the LUT settings. However, in neither case was it possible to find a link between soft tissue type and Hounsfield units.
We have been using µCT for a long time and we need to visualize soft tissues in experimental animals. For a long time, there is a tradition of contrast agent usage, but they are not always best and/or we often encounter problems when using them. This is why we tried to figure out some connection between LUT setting and HU values for individual structures and organs; even mentioned contrast agents could have been of some value in this. Additionally, we wanted to find out if there exist other possibilities of contrast enhancement, e.g., because of air bubbles in contrast agent for ultrasound. Especially this is considered when experimenting with PHYWE XR 4.0 in various structures in chicken tissues (phantom). Finally, we also think about semiautomated, or fully automated settings of LUT with fuzzy logic. Some of these ideas were verified within this study.
The main aim of this study is to optimize soft tissue contrast visualization of biological specimens (mouse liver, kidneys) using a contrast agent and a proper LUT. Based on this aim we would like to statistically verify the relationship between the centroid of the area under the look-up-table curve and the number of days for which the animal sample was stored in the ethanol solution, as well as the concentration of the ethanol solution. Therefore, two hypotheses were formulated. H1 (Each occurrence of H1 means that it is an allernative hypothesis) of the first hypothesis states that the Spearman's correlation coefficient does not equal zero (r 1 = 0) in the case of relationship between the coordinates of the center of gravity (centroid) of the area under the LUT and the number of days for which the sample was stored in the ethanol solution. H1 of the second hypothesis states that the Spearman's correlation coefficient does not equal zero (r 2 = 0) in the case of relationship between the coordinates of the center of gravity (centroid) of the area under the LUT and the ethanol concentration in the solution.

Materials, Devices, and Software
The database of µCT images from the Dept. of Anatomy of the 3rd Medical Faculty of Charles University was used for the study.
All intravenous contrast agent's applications follow similar pattern. At first there is introduced the contrast agent into the tail vein. After that follows animal euthanasia and µCT scanning. Concerning Aurovist contrast agent, solution from the ampoule is injected into tail vein under isoflurane anesthesia into the bloodstream. Follows scanning in the µCT apparatus. Concerning the timing, scanning is performed after complete distribution of Aurovist gold nanoparticles to the tissues of the animal, including both arteries and veins of the circulatory system.
Preparation steps for experimental animals were the following.
Animals (mice) were housed in the standard light/dark cycle in the First Faculty of Medicine, Charles University at standard room temperature. Mice were applied one ampulla of Aurovist contrast agent (15 nm of Aurum particles in 40 mg of solution, Nanoprobes, Yaphank, NY, USA) in the tail vein per one mouse. In case of whole mouse experiment, 2 h after Aurovist application were mice euthanized with pentobarbital and scanned in micro-CT. Timing was selected because rigor mortis develops within 2 h after death.
Animals (chickens) were obtained by micro-surgery from the eggs in their 19 days of development. Firstly, a rectangular window was dissected out of the egg wall and solution of 40% KI to euthanize chicken (heartbeat stop) was applied intra-amniotically. After the removal of dead chicken from the egg it was placed into 80% of Ethanol for 7 days.
Animals (rabbits) were donated by Prof. Berndt Minnich, University of Salzburg, Vascular Unit, Austria. Post-mortem, rabbits were pinned in supine position onto a wax plate. After opening of the abdomen, the aorta abdominalis was identified and separated from each other. A ligature around the aorta abdominalis ensured exclusive upper body casting. A tube was inserted into the artery cranially to the first ligature and tied in place (6.0 sutures). Blood vessels were rinsed after opening the aorta with 0.9% Ringer's solution (60 mL/h) at 37 • C until clear reflux appeared. Thereafter, the casting medium (Mercox-Cl-2B, Ladd Research Inc., Burlington, VT, USA) diluted with monomeric methyl methacrylate was injected at 99 mL/h by an electric syringe pump (Habel PSA 50, Sky Electronics S.A., Grenoble, France) or a pneumatic injection pump (ComServ OG, Ebenau, Austria). When the injected resin became viscous, animals were left in place for at least 30 min at room temperature (RT) to initiate resin polymerization. The upper bodies of the rabbits were cut off and tempered in water (60 • C, 24 h). Subsequently, water was replaced by potassium hydroxide (7.5%, 40 • C, twice for 24 h), followed by hydrochloric acid (2%, RT, 24 h) and formic acid (5%, RT, 15 min). Finally, casts were washed thrice and frozen in distilled water (−20 • C) and freeze-dried (FreeZone 77520, Labconco Corp., Kansas City, MO, USA).
The database consisted of ex vivo chickens in and out of the shell and aged 5 to 19 days. Chickens outside the shell were preserved in 50-100% ethanol solution, some of them additionally in formaldehyde solution. In addition, a few chicken samples contained injected gold nanoparticles from the Aurovist contrast agent. Prior to acquisition, samples were left in air after removal from the solution and scanned with Bruker's SkyScan 1275 (Bruker MicroCT, Kontich, Belgium) after evaporation of the solution.
Another part of the database consisted of ex vivo preparations of mice injected with Aurovist contrast agent containing 15 nm gold nanoparticles (AuNPs) prior to scanning.
A 50% solution of Omnipaque contrast agent was then used intravenously before scanning the mouse organs themselves (liver, lungs, spleen, and heart).
Some mouse organs, such as liver, kidney, brain, heart, and leg, were kept for one week in a solution of potassium iodide with concentration 100 mM (KI, Merck, Czech Republic) in 20% ethanol before scanning.
Lastly, the database included corrosive preparations in which a resin (Mercox) [10] was infused into the vascular system and allowed to harden, the remaining tissue was then dissolved in lye by maceration and the sample was scanned. Corrosive preparations of rabbit and rat lung and heart were selected for the purpose of this study.
For the implementation of the idea of blood vessels visualization in soft tissue using the contrast that would be created by the presence of air in the vascular cavities, chicken flesh was used as a phantom in which cylindrical tubes/capillaries of various diameters made of different materials were placed. These were two tubes (silicone), a glass capillary with sealed ends, and a plastic straw (bioplastic PLA). This phantom, depicted in Figure 1, was then scanned with the Phywe XR 4.0 (PHYWE Systeme GmbH & Co. KG, Göttingen, Germany) experimental setup. Appl. Sci. 2022, 12, x FOR PEER REVIEW 4 of 36 with sealed ends, and a plastic straw (bioplastic PLA). This phantom, depicted in Figure  1, was then scanned with the Phywe XR 4.0 (PHYWE Systeme GmbH & Co. KG, Göttingen, Germany) experimental setup. Two µ CT systems were used to scan the above samples. The ex vivo chicken samples were scanned with a professional µ CT system Bruker SkyScan 1275 located at the Department of Anatomy, 3rd Faculty of Medicine, Charles University, while the Phywe XR 4.0 experimental setup was used to scan the phantom of the chicken vasculature and capillaries at the Dept. of Biomedical Technology, Fac. of Biomedical Engineering, Czech Technical University in Prague.
Bruker's SkyScan 1275 has been specifically designed for fast scanning using advances in X-ray source technology and efficient flat-panel detectors. This X-ray source has the selectable anode voltage of the assembly ranging from 20 to 100 kV and the max. available power is 10 W. The assembly includes an active 3 megapixel CMOS flat-panel detector with a maximum possible resolution of up to 4 μm (at maximum magnification) and it is capable of accommodating a sample diameter of 96 mm and a height of 120 mm. All used setups of the above mentioned µ CT are available within the Appendix B, i.e., Tables A2-A19.
The XR 4.0 experimental setup from the German company Phywe was designed for teaching purposes and for laboratory experiments with X-rays. Its advantage lies, among other things, in the relatively easy and quick interchangeability of the X-ray tube and, therefore, facilitates experiments with different anode materials [11,12].
The XR 4.0 can also be used as a µ CT system thanks to an expansion kit supporting the computed tomography function. This set consists of a fixed copper X-ray tube that illuminates the specimen on a rotary table driven by a stepper motor with a minimum adjustable table rotation angle of 0.086°. The attenuated X-ray radiation is then incident on an XRIS detector (CMOS) with an active area of 5 × 5 cm 2 and a maximum possible resolution of 48 μm [11,12]. The selectable anode voltage of the assembly is 5-35 kV with Two µCT systems were used to scan the above samples. The ex vivo chicken samples were scanned with a professional µCT system Bruker SkyScan 1275 located at the Department of Anatomy, 3rd Faculty of Medicine, Charles University, while the Phywe XR 4.0 experimental setup was used to scan the phantom of the chicken vasculature and capillaries at the Dept. of Biomedical Technology, Fac. of Biomedical Engineering, Czech Technical University in Prague.
Bruker's SkyScan 1275 has been specifically designed for fast scanning using advances in X-ray source technology and efficient flat-panel detectors. This X-ray source has the selectable anode voltage of the assembly ranging from 20 to 100 kV and the max. available power is 10 W. The assembly includes an active 3 megapixel CMOS flat-panel detector with a maximum possible resolution of up to 4 µm (at maximum magnification) and it is capable of accommodating a sample diameter of 96 mm and a height of 120 mm. All used setups of the above mentioned µCT are available within the Appendix B, i.e., Tables A2-A19.
The XR 4.0 experimental setup from the German company Phywe was designed for teaching purposes and for laboratory experiments with X-rays. Its advantage lies, among other things, in the relatively easy and quick interchangeability of the X-ray tube and, therefore, facilitates experiments with different anode materials [11,12].
The XR 4.0 can also be used as a µCT system thanks to an expansion kit supporting the computed tomography function. This set consists of a fixed copper X-ray tube that illuminates the specimen on a rotary table driven by a stepper motor with a minimum adjustable table rotation angle of 0.086 • . The attenuated X-ray radiation is then incident on an XRIS detector (CMOS) with an active area of 5 × 5 cm 2 and a maximum possible resolution of 48 µm [11,12]. The selectable anode voltage of the assembly is 5-35 kV with an adjustable emission current in the range up to 1 mA. Setup with detailed setting is available within the Appendix B, i.e., Table A1.

Methods
In the field of digital image data processing (digital images), various point operators or functions are very often used to perform single-point assignment, or transform the value of an image point (pixel) from an input image (labeled a) at a given position (x, y) to another value within the output image (labeled b), but at the same position (x, y). In general, this situation is indicated in Figure 2.
an adjustable emission current in the range up to 1 mA. Setup with detailed setting is available within the Appendix B, i.e., Table A1.

Methods
In the field of digital image data processing (digital images), various point operators or functions are very often used to perform single-point assignment, or transform the value of an image point (pixel) from an input image (labeled a) at a given position (x, y) to another value within the output image (labeled b), but at the same position (x, y). In general, this situation is indicated in Figure 2.  Table Concept Let us consider an experiment where we multiply the pixel values in the input image by 1. If we consider the usual input dynamic range of grayscale digital images (i.e., 0 to 255, where 0 represents the black level and 255 represents the white level), then the output image will produce a result that is identical to the values in the input image. For example, an input value of 10 would be multiplied by 1 and the result would also be 10 and this would continue for all pixel values in all positions. This then results in a simple linear function that can be represented as a straight line at a 45° angle and passing through the origin of the coordinates, or it is a simple copy of the input image. Such an example can also be expressed very simply in mathematical notation, namely the slope equation of the straight line as reported in Figure 3.  Table Concept Let us consider an experiment where we multiply the pixel values in the input image by 1. If we consider the usual input dynamic range of grayscale digital images (i.e., 0 to 255, where 0 represents the black level and 255 represents the white level), then the output image will produce a result that is identical to the values in the input image. For example, an input value of 10 would be multiplied by 1 and the result would also be 10 and this would continue for all pixel values in all positions. This then results in a simple linear function that can be represented as a straight line at a 45 • angle and passing through the origin of the coordinates, or it is a simple copy of the input image. Such an example can also be expressed very simply in mathematical notation, namely the slope equation of the straight line as reported in Figure 3.  With this defined operator, we can easily adjust various changes to image parameters such as brightness and contrast, both when we need to highlight selected gray levels or when we need to suppress them. Examples of different transfer functions are shown in Figures 4 and 5. With this defined operator, we can easily adjust various changes to image parameters such as brightness and contrast, both when we need to highlight selected gray levels or when we need to suppress them. Examples of different transfer functions are shown in  Example of a point operator (function) that implements a copy of the input image on the output. In this case, the value of the slope (i.e., k = 1), and the value of the y-intercept of a straight line where a line crosses y-axis of a graph (i.e., q = 0).
With this defined operator, we can easily adjust various changes to image parameters such as brightness and contrast, both when we need to highlight selected gray levels or when we need to suppress them. Examples of different transfer functions are shown in Figures 4 and 5.   From the above examples, it is clear that these transfer functions or LUTs allow to significantly influence the visualization process of the given image data. Thus, for example, the transfer function in Figure 4 (panel 2) affects the brightness of the image, in Figure 4 (panel 3) it affects the contrast, in Figure 4 (panel 6) a transfer function for realizing a socalled binary image (i.e., an image that contains only two levels, most often black and white) is shown, and yet another suitable example can be seen in Figure 5 (panel 12), which is suitable for correcting an image that was taken under greatly reduced or increased lighting conditions. The latter two examples are further illustrated in the image data, respectively, in Figures 6 and 7. From the above examples, it is clear that these transfer functions or LUTs allow to significantly influence the visualization process of the given image data. Thus, for example, the transfer function in Figure 4 (panel 2) affects the brightness of the image, in Figure 4 (panel 3) it affects the contrast, in Figure 4 (panel 6) a transfer function for realizing a so-called binary image (i.e., an image that contains only two levels, most often black and white) is shown, and yet another suitable example can be seen in Figure 5 (panel 12), which is suitable for correcting an image that was taken under greatly reduced or increased lighting conditions. The latter two examples are further illustrated in the image data, respectively, in Figures 6 and 7.

Transfer Functions Related to the Hounsfield Units (HU)
There is a very important process in CT and µ CT imaging, that is the actual conversion of the attenuation of the passing X-rays to the grey level. Based on the physiological properties of human vision, 256 gray levels are very often used. The range of so-called Hounsfield units (HU) is typically in the range −1024 to +3071, which is 4096 values, and this is a much larger dynamic range than the 256 gray level values. For this reason, only the so-called windows on a given tissue (limited HU range), which has a width of 256 values or greater, need to be displayed. Thus, it is never possible to see all tissues at once, see soft tissue window, bone window, etc. Realistically, this situation is often implemented by a transfer function that has HU values on the x-axis and gray level values from 0 to 255 on the vertical axis. The situation is also depicted in Figure 8, which is an example of this situation in NRecon software [15].

Transfer Functions Related to the Hounsfield Units (HU)
There is a very important process in CT and µCT imaging, that is the actual conversion of the attenuation of the passing X-rays to the grey level. Based on the physiological properties of human vision, 256 gray levels are very often used. The range of so-called Hounsfield units (HU) is typically in the range −1024 to +3071, which is 4096 values, and this is a much larger dynamic range than the 256 gray level values. For this reason, only the so-called windows on a given tissue (limited HU range), which has a width of 256 values or greater, need to be displayed. Thus, it is never possible to see all tissues at once, see soft tissue window, bone window, etc. Realistically, this situation is often implemented by a transfer function that has HU values on the x-axis and gray level values from 0 to 255 on the vertical axis. The situation is also depicted in Figure 8, which is an example of this situation in NRecon software [15].
values, and this is a much larger dynamic range than the 256 gr reason, only the so-called windows on a given tissue (limited H width of 256 values or greater, need to be displayed. Thus, it is tissues at once, see soft tissue window, bone window, etc. Real often implemented by a transfer function that has HU values on values from 0 to 255 on the vertical axis. The situation is also dep is an example of this situation in NRecon software [15].  The practical impact of this situation is also the arrangement of the image data format in the form of so-called DICOM (Digital Imaging and Communications in Medicine) files. This file contains both image data and metadata [17] and each DICOM browser can display both. The structure of DICOM files consists of so-called tags and an example of these tags in relation to HU are the following items (i.e., the DICOM attribute number (0028,1053) whose name is "Rescale slope" and the DICOM attribute number (0028,1052) whose name is "Rescale intercept"). These parameters can then be substituted into the equation after the parameters k and q in Figure 3. These items can also be read.

Transfer Functions Design Possibilities
Within the Ctvox software a histogram of the attenuation is available together with an editor that can be used to freely modify the transfer functions as LUTs, i.e., the program can either simply connect individual markers or use them as nodes to create a so-called spline curve. The program then assigns to each voxel the corresponding degree of the currently selected parameter (the so-called emission color [18]) depending on the attenuation of the voxel in the spline mode called volume rendering.
There are five parameters to choose from-opacity, red (R) channel, green (G) channel, blue (B) channel, and luminance (L), as reported in Figure 9c. If all three RGB channels are combined, only two parameters are available (i.e., opacity and luminance), and the voxels are assigned to their opacity and grayscale. In the other case, four parameters are available, namely, opacity together with all three RGB channels. In addition to assigning opacities, individual voxels can also be colored differently in this way, or segmented by color. In the case of opacity, there is available a purple opacity curve (initially a straight line, with just two markers) appears, in order to indicate that it is active. Opacity is the opposite of transparency. Hence, we will need to map low intensities to low opacities (i.e., high transparency), as shown in Figure 9c.
program can either simply connect individual markers or use them as nodes to create a so-called spline curve. The program then assigns to each voxel the corresponding degree of the currently selected parameter (the so-called emission color [18]) depending on the attenuation of the voxel in the spline mode called volume rendering.
There are five parameters to choose from-opacity, red (R) channel, green (G) channel, blue (B) channel, and luminance (L), as reported in Figure 9c. If all three RGB channels are combined, only two parameters are available (i.e., opacity and luminance), and the voxels are assigned to their opacity and grayscale. In the other case, four parameters are available, namely, opacity together with all three RGB channels. In addition to assigning opacities, individual voxels can also be colored differently in this way, or segmented by color. In the case of opacity, there is available a purple opacity curve (initially a straight line, with just two markers) appears, in order to indicate that it is active. Opacity is the opposite of transparency. Hence, we will need to map low intensities to low opacities (i.e., high transparency), as shown in Figure 9c.

Results
A total of 53 transfer functions (LUTs) were designed, 42 of which were validated and optimized to emphasize the soft tissues of selected biological samples from µ CT (mouse, rat, rabbit) using selected contrast agents (Aurovist, Omnipaque, KI in the ethanol solution, Mercox). The remaining 11 transfer functions could not be verified due to the absence of contrast in soft tissue samples from chickens. In total, 18 images and transfer functions are included within this text.

Results
A total of 53 transfer functions (LUTs) were designed, 42 of which were validated and optimized to emphasize the soft tissues of selected biological samples from µCT (mouse, rat, rabbit) using selected contrast agents (Aurovist, Omnipaque, KI in the ethanol solution, Mercox). The remaining 11 transfer functions could not be verified due to the absence of contrast in soft tissue samples from chickens. In total, 18 images and transfer functions are included within this text.
Out of the 53 transfer functions, one transfer function was able to be suggested that would likely highlight the tongue of a 19-day-old chick scanned with the Bruker SkyScan 1275 [19] at an anode voltage of 40 kV.
A total of 24 mice samples were statistically processed via correlation. Normality test was performed for all these samples in Matlab (Campus Wide Matlab, R2021a, The MathWorks, Inc., Natick, MA, USA) via Lilliefors test. These values were obtained for liver and kidneys of 24 mice in solutions of ethanol as a centroid value of the opacity LUT area under this graph (see example on Figure 10). Except for one dataset, all the others do not have a normal distribution according to this test. Results are available within Tables 1-4 below. From this follows that there is required to use Spearman s correlation coefficient.
In Figure 10 test was performed for all these samples in Matlab (Campus Wide Matlab, R2021a, The MathWorks, Inc., Natick, MA, USA) via Lilliefors test. These values were obtained for liver and kidneys of 24 mice in solutions of ethanol as a centroid value of the opacity LUT area under this graph (see example on Figure 10). Except for one dataset, all the others do not have a normal distribution according to this test. Results are available within Tables 1-4 below. From this follows that there is required to use Spearman´s correlation coefficient.     [20]. In case of a homogenous triangle, the resulting centroid's x coordinate is the average of the x coordinates of its vertices.  The hypotheses mentioned within the Introduction were evaluated based on these data. This was a test of the alternative hypothesis that the Spearman correlation coefficient is not equal to 0. We used a relationship (see link within the [21]) where, given H0: r = 0, the t Student's statistic has a distribution with d.f. (degree of freedom): N-2 (see also link within the [22]). Overall, 18 LUTs from 53 LUTs were also validated on selected biological samples, selection of which is illustrated within this section and reported in Figures 9 and 11 -13. Figures A1 to A18. Part A1 (Figures A1 and A2) is related to the ethanol contrast, part A2 ( Figures A3-A7) to Aurovist, part A3 ( Figures A8-A11) to Omnipaque, part A4 ( Figures  A12-A16) to potassium iodide (KI) in 20% ethanol solution and part A5 (Figures A17 and  A18) to Mercox resin. Captions of these figures content detailed descriptions of all possible findings due to the better contrast visualization. It is the reason why these figures are included with higher spatial resolution within the Appendix A.   with more details according to the contrast agent used, in Appendix A, specifically in Figures A1 to A18. Part A1 (Figures A1 and A2) is related to the ethanol contrast, part A2 ( Figures A3-A7) to Aurovist, part A3 ( Figures A8-A11) to Omnipaque, part A4 ( Figures  A12-A16) to potassium iodide (KI) in 20% ethanol solution and part A5 (Figures A17 and  A18) to Mercox resin. Captions of these figures content detailed descriptions of all possible findings due to the better contrast visualization. It is the reason why these figures are included with higher spatial resolution within the Appendix A.

Discussion
The main finding of this study is that there is a statistically significant monotonic relationship between the centroid of the area under the LUT curve and the number of days for which the animal sample was stored in the ethanol solution. H1 of the first hypothesis that the Spearman's correlation coefficient does not equal zero (r1 ≠ 0) regarding this relationship was confirmed. On the other hand, there is no statistically significant monotonic relationship between the centroid of the area under the LUT curve and the concentration of the ethanol solution, see Tables 1-4. In this case, H1 of the second hypothesis that the Spearman's correlation coefficient does not equal zero (r2 ≠ 0) regarding this relationship was not confirmed. Within Table 4, we can see relevant average values for selected storage days of the specimen and related Hounsfield units, i.e., CT numbers as well. These values are very important and can be assigned to the centroid parameters of a LUT curve incorporating the relevant parameter of days for which the animal sample (mouse liver or kidney) was stored in ethanol solution.
Another finding of the study is that it is not possible to use one universal transfer function for proper soft tissue visualization of µ CT images. The use of an appropriate contrast agent has a very significant effect on soft tissue visualization. It was possible to visualize the capillaries inside the chicken flesh in the phantom vasculature. In the case of the mouse heart, it was possible to segment and colorfully distinguish the tissue of the heart muscle from the rest of the blood vessels.
Due to the lack of one optimal and universal transfer function (LUT), a total of 53 transfer functions were designed using CTvox software [13] and optimized to highlight soft tissues in particular.
In the case of the mouse liver, mainly its external structures can be seen, while in the case of the kidney, brain, and heart, the internal structures are partially visible. In the mouse leg specimen, the transfer function emphasizes partly soft tissue and partly hard tissue (bone).
For the corrosive preparations, the soft tissue structures are shown by the contrast created between the Mercox resin and the air. Since the CT numbers of the synthetic resin are around 70 HU [2], it is possible to speak of a soft tissue equivalent in this case (range 40-80 HU).

Discussion
The main finding of this study is that there is a statistically significant monotonic relationship between the centroid of the area under the LUT curve and the number of days for which the animal sample was stored in the ethanol solution. H1 of the first hypothesis that the Spearman's correlation coefficient does not equal zero (r 1 = 0) regarding this relationship was confirmed. On the other hand, there is no statistically significant monotonic relationship between the centroid of the area under the LUT curve and the concentration of the ethanol solution, see Tables 1-4. In this case, H1 of the second hypothesis that the Spearman's correlation coefficient does not equal zero (r 2 = 0) regarding this relationship was not confirmed. Within Table 4, we can see relevant average values for selected storage days of the specimen and related Hounsfield units, i.e., CT numbers as well. These values are very important and can be assigned to the centroid parameters of a LUT curve incorporating the relevant parameter of days for which the animal sample (mouse liver or kidney) was stored in ethanol solution.
Another finding of the study is that it is not possible to use one universal transfer function for proper soft tissue visualization of µCT images. The use of an appropriate contrast agent has a very significant effect on soft tissue visualization. It was possible to visualize the capillaries inside the chicken flesh in the phantom vasculature. In the case of the mouse heart, it was possible to segment and colorfully distinguish the tissue of the heart muscle from the rest of the blood vessels.
Due to the lack of one optimal and universal transfer function (LUT), a total of 53 transfer functions were designed using CTvox software [13] and optimized to highlight soft tissues in particular.
In the case of the mouse liver, mainly its external structures can be seen, while in the case of the kidney, brain, and heart, the internal structures are partially visible. In the mouse leg specimen, the transfer function emphasizes partly soft tissue and partly hard tissue (bone).
For the corrosive preparations, the soft tissue structures are shown by the contrast created between the Mercox resin and the air. Since the CT numbers of the synthetic resin are around 70 HU [2], it is possible to speak of a soft tissue equivalent in this case (range 40-80 HU). Unfortunately, it was not possible to properly visualize soft tissues or organs from any of the chick scans. In fact, it is not certain that the scan of a stained chicken head of a 19-day-old chick at an anode voltage of 40 kV succeeded in highlighting just the tongue of this chick, or whether it is only the cartilaginous part of its beak.
In ex vivo samples of chickens prepared in ethanol and formaldehyde solutions, there was a presumption of contrast in the µCT images through protein coagulation. This assumption was probably only partially borne out and the result shows the interior of the chicken stained differently in blue and red, corresponding to a slight difference in CT numbers of otherwise further visualizable soft tissue. Furthermore, the ethanol solution in whole chickens did not have the opportunity to penetrate and subsequently evaporate from the animal cavities, which would have caused the solution to be replaced by air, which would have further caused better contrast in the µCT images (comparable to the evaporation of ethanol from the cavities of the animal organs evaporated therein).
It is also interesting to note that the plastic straw made of polyethylene has approximately the same CT number as the chicken meat and therefore cannot be distinguished from the meat as it passes through it. The glass capillary was the best of all materials to see, as the glass-air interface is a very high contrast object against soft tissue. This was followed by a larger diameter silicone capillary and the third was a smaller diameter capillary. Thus, in contrast to polyethylene, all other materials were clearly distinguishable from chicken meat (Figure 1).
In the majority of cases, the output of CTvox shows that using a lower anode voltage is the optimal choice for scanning soft tissue on µCT. In the case of bone segmentation, the choice of voltage did not play any significant role. For a more prominent presentation of the results, the processing of the oldest chicks prepared in ethanol was deliberately chosen, mainly because the chick is not sufficiently anatomically developed until around day 19 after egg fertilization, as this is the age at which chicks usually hatch. When younger chicks were examined, many structures were not yet sufficiently developed and, therefore, not visible.
Four chicken samples also contained the contrast agent Aurovist, consisting of 15 nm gold nanoparticles. Specifically, there were two scans at 10 days of age and another two at 12 days of age; unfortunately, no internal (soft) anatomical structures could be identified in this case either. This may have been due to the short age of the chicks, which may not have developed these structures properly yet. A second explanation could be that very low amount of Aurovist contrast agent was injected into the sample.
The limitation of this study is the relatively small number of included images and contrast agents. Another limitation is the use of the purely experimental-based level of visualization, i.e., there is subjective dependence of operator and possible variable deviation. In the case of statistical processing of the data with different KI concentrations, only two different concentrations were used-50% and 100%-this was a limitation, also.

Conclusions
In addition to the contrast agents used above, there is possible to use other more suitable contrast agents with very interesting properties. The idea is to perform next study based on the optimal contrast agent selection with relevant LUT. There are prepared comparative experiments with the set of such contrast agents as Sonovue, Iomeron, Optison, Omnipaque, Visipaque, Xenetix, Optiray, and Ultravist to be able to select appropriate one. However, there is assumed utilization of the semi-automatic/automatic LUT setup.

Informed Consent Statement: Not applicable.
Data Availability Statement: The complete original data are not publicly available due to large volume. However, there are available all LUTs as images and *.tf files and relevant images as well. Please, use the link within the [23].
Acknowledgments: There were used uncommercial licenses of software measure CT from Phywe [11,12], CTvox [13] and NRecon [15] from Bruker and Dragonfly [14] from ORS. We would like to thank Phywe, Bruker, and Object Research Systems for their kind support and feedback.

Conflicts of Interest:
The authors declare no conflict of interest.

Appendix A
After reconstructing the data with NRecon, we designed several transfer functions in CTvox to emphasize the different structures of the selected samples, especially soft tissues. The CTvox outputs are divided into 5 subsections-according to the method of sample preparation or contrast used. This appendix is an additional section that contains details and data supplemental to the main text above (see the Results section). Figures of replicates for experiments of which representative data are shown in the main text above are added here with higher spatial resolution and detailed description.  Acknowledgments: There were used uncommercial licenses of software measure CT from Phywe [11,12], CTvox [13] and NRecon [15] from Bruker and Dragonfly [14] from ORS. We would like to thank Phywe, Bruker, and Object Research Systems for their kind support and feedback.

Conflicts of Interest:
The authors declare no conflicts of interest.

Appendix A
After reconstructing the data with NRecon, we designed several transfer functions in CTvox to emphasize the different structures of the selected samples, especially soft tissues. The CTvox outputs are divided into 5 subsections-according to the method of sample preparation or contrast used. This appendix is an additional section that contains details and data supplemental to the main text above (see the Results section). Figures of replicates for experiments of which representative data are shown in the main text above are added here with higher spatial resolution and detailed description.

Appendix A.2. Aurovist
In ex vivo mice with a gold nanoparticles contrast agent (Aurovist), we have designed transfer characteristics/functions that colorfully highlight soft tissue structures, particularly in blood vessels and airways. Figure A2. Dyed 19-day-old chicken (acquisition at anode voltage 40 kV, contrast agent ethanol). Imaging after 5 days of ethanol fixation with incipient soft tissue contrast of the trachea, diaphragm, and heart muscle. The contrast in this phase of fixation also corresponds to the density of the surface structures of skin derivatives (feathers).

Appendix A.2. Aurovist
In ex vivo mice with a gold nanoparticles contrast agent (Aurovist), we have designed transfer characteristics/functions that colorfully highlight soft tissue structures, particularly in blood vessels and airways. Here, is clearly visible the vasculature of the kidneys and their placement in the retroperitoneum on the sagittal section, the vessels of the thoracic organs, the hepatic vessels of all lobes, and the supply of the intestines in the abdominal cavity and pelvic plexus. In the section at the level of the thorax, there is a detail of the pulmonary system, where, according to the symmetry of the distribution and branching of the vessels, we can also describe their loss due to occlusion. Figure A3. The Aurovist intravascular contrast displayed the entire vascular bed of the mouse. Here, is clearly visible the vasculature of the kidneys and their placement in the retroperitoneum on the sagittal section, the vessels of the thoracic organs, the hepatic vessels of all lobes, and the supply of the intestines in the abdominal cavity and pelvic plexus. In the section at the level of the thorax, there is a detail of the pulmonary system, where, according to the symmetry of the distribution and branching of the vessels, we can also describe their loss due to occlusion.
Appl. Sci. 2022, 12, x FOR PEER REVIEW 18 of 36 Figure A4. Color resolution of mouse vessels on the body surface (red) and internal organs (green). This distinction also offers a comprehensive view important for the orientation and description of superficial and parietal vessels. In the head area is visible in the external carotid artery branching, then interscapular brown fat vessels, superficial thoracic branching of the thoracic artery and intercostal vessels, parietal lumbar and sacral vessels, as well as plexuses around the spinal canal and limb vessels. The blood vessels of the kidneys and liver here form a network corresponding to the location of the organs in the abdominal cavity, the blood vessels of the heart and lungs to the organs in the chest. This arrangement allows the vessels to be compared at different topographic sites in the body. Figure A4. Color resolution of mouse vessels on the body surface (red) and internal organs (green). This distinction also offers a comprehensive view important for the orientation and description of superficial and parietal vessels. In the head area is visible in the external carotid artery branching, then interscapular brown fat vessels, superficial thoracic branching of the thoracic artery and intercostal vessels, parietal lumbar and sacral vessels, as well as plexuses around the spinal canal and limb vessels. The blood vessels of the kidneys and liver here form a network corresponding to the location of the organs in the abdominal cavity, the blood vessels of the heart and lungs to the organs in the chest. This arrangement allows the vessels to be compared at different topographic sites in the body.     Here, is a physiological finding. According to the drawing of the vasculature, we can also describe possible pathological conditions, reconstruction of the liver parenchyma, and its irregular vascular bed or proliferation of blood vessels in tumors.             For corrosive slides, transfer characteristics/functions emphasizing only the soft tissue structures (not the soft tissue itself) have been proposed using a contrast between resin and air. The images show the rabbit and rat airways, and in the case of the rat, the heart is visible along with the vasculature as well. For corrosive slides, transfer characteristics/functions emphasizing only the soft tissue structures (not the soft tissue itself) have been proposed using a contrast between resin and air. The images show the rabbit and rat airways, and in the case of the rat, the heart is visible along with the vasculature as well.   Figure A18. The corrosive specimen of the heart and blood vessels shows both the coronary arteries for the heart, the basic platform for incipient myocardial infarction, and the branching of the pulmonary artery and pulmonary artery diameters and their angles of spacing and segmentation.
Here, is a physiological finding. The arrangement of the pulmonary arteries and their branching is disturbed in pulmonary embolism, vascular wall pathology and also in lung tumors.

Appendix B
This appendix is an additional section that contains details and data supplemental to the main text from the point of view of the experimental setting of both setups, i.e., Phywe and Bruker systems.

Parameter
Value Physical Unit object-source distance 310 mm Figure A18. The corrosive specimen of the heart and blood vessels shows both the coronary arteries for the heart, the basic platform for incipient myocardial infarction, and the branching of the pulmonary artery and pulmonary artery diameters and their angles of spacing and segmentation.
Here, is a physiological finding. The arrangement of the pulmonary arteries and their branching is disturbed in pulmonary embolism, vascular wall pathology and also in lung tumors.

Appendix B.
This appendix is an additional section that contains details and data supplemental to the main text from the point of view of the experimental setting of both setups, i.e., Phywe and Bruker systems. The scan settings for scanning biological samples of chickens outside the shell with the SkyScan 1275 are shown in the following tables. The table header consists of a number followed by a capital letter D, this is the age of the chicken, which is given in days. This may be preceded either by another number followed by the capital letter E, in which case it is the concentration of the ethanol solution in which the chicken was prepared, or by the letter F, which indicates that the chicken was prepared in a formaldehyde solution. In four cases, the concentration of the Ethanol solution is preceded by the capital letter A, this is the contrast agent Aurovist.      The scanning parameters for scanning biological samples of chickens in the shell with the SkyScan 1275 are shown in the following tables. The table header consists of a number followed by a capital letter D, this is the age of the chicken, which is given in days.        The scan settings for scanning mouse biological samples with Aurovist contrast agent (letter A), rabbit and rat biological samples with Mercox resin contrast agent (letter M), and mouse organ biological samples with Omnipaque contrast agent (letter O) and potassium iodide (KI) contrast agent dissolved in 20% ethanol solution (letters KI) with the SkyScan 1275 kit are shown in the following tables.