Viruses appear in various sizes and forms, but each viral family has unique features. SARS-CoV-2 is similar in architecture to other known human CoVs. For example, a nucleic acid genome is inside a protective coating of proteins known as a capsid in every virus except the spike portion responsible for binding the host cell-surface receptor during host cell entry. Results show the spike protein and envelope components as significant features in the coronavirus family(Yutin et al. 2021). In some cases, viral may look similar, but their structure (envelope diameter, length, and density of spike portion) differs. A published report shows that SARS-CoV-2 has 79.5% similarity to SARS-CoV and 50% similarity to MERS-CoV(Zhu et al. 2020b).It appears to be only slightly different from SARS-CoV in terms of clinical features. However, it is spreading even faster [40],[41]. Virus particles have rounded or oval shapes in their surface appearance. However, in each image, some particles were a different, irregular, or deformed shape; for this reason, they were excluded from the morphometric assessment. There were differences in the size distribution of SARS-CoV and SARS-CoV2. It is vital to emphasize that in many countries, computed tomography is the most commonly utilized medical imaging modality for diagnosing SARS-CoV-2; due to its widespread use, databases are now available to researchers. However, there are many difficulties, such as ground-glass opacities, consolidation, and bizarre paving patterns. These problems can be viewed alone or in combination with one another. It suggests that while chest CT is very sensitive, it is not highly specific for COVID-19. Therefore, patients who get these findings should have a more thorough clinical examination and laboratory tests to rule out other possible reasons(Schultz et al. 2020),(Chen et al. 2020),(Huang et al. 2021). In this work, we use ImageJ (Fiji) software extraction to analyse these features, a broad selection method focusing on biological-image analysis to enable fast image processing methods. (Schindelin et al. 2012), We examined a dataset collection of TEM images containing 515 images of SARS-CoV2 and 248 SARS-CoV particles in ultrathin plastic slices of infected Vero cultured cells.
4.1. Assessment of envelope diameter
A study evaluated that the SARS-CoV 2 diameter varied from about 60 to 140 nm as observed under a transmission electron microscope(Zhu et al. 2020a). In contrast to what was seen before, our assessment differs considerably in identifying the envelope diameter of the virus. Extracting the features of the virus diameter is essential for the SARS-CoV2 identifiers in our system and we measured the diameter sizes from various EM images using ImageJ software. In order to evaluate images, we may have to compensate for recording errors. Noise, uneven lighting, and background fluorescence can cause a variety of image processing problems. In the first stages, we apply enhancement contrast on the images to show the shape outlier of a virus, then applied the scale bar tool and the measurement option closely fit to choose the outer layer of the viral envelope. Figure 6, shows the TEM morphology features of the envelope protein distribution diameter for both SARS-CoV2 and SARS-CoV viruses, and we adjusted scale bars "Straight Line" tool at 100 nm. Consequently, the average diameter for SARS-CoV2 and SARS-CoV was 97 nm and 102 nm, respectively. The Gaussian Distribution uses the numerical correlation that explains values in a data collection, and measurements approximate this connection as sample size expands. The diameter of an envelope is based on the mean and standard deviation of a given Gaussian distribution. The mean defines the location of the curve's center, whereas the standard deviation determines its apparent breadth.
4.2. Assessment of length spike protein
In this part we extracted the average length peak of SARS-CoV2 and SARS-CoV. We also measured the tip length with the ImageJ software with the scale bar tool at 12 nm. Many studies described the length of virus spikes protein, around (9-12) nm in size, which gave virions the appearance of a solar corona (Zhu et al. 2020a). In addition, the architecture observed is compatible with the coronavirus family. Cryo-EM images of isolated SARS-CoV-2 virions revealed the existence of virus tips and membranes. About 20%-30% of virions have multiple spines around the membrane, while most other virus particles have few spikes(Liu et al. 2020). However, we tested many tip lengths of various images to prove the main length using the scale bar tool in ImageJ software. Figure 7, Illustrate the distribution average spike length using TEM images and the adjusted scale bars "Straight Line" tool at 12 nm and the Gaussian distribution of SARS-CoV 2 and SARS-CoV spike protein with probability density of spikes length. The results indicate that the average spike length for SARS-CoV 2 SARS-CoV was 11.5 nm 11.2 nm, respectively.
4.3. Assessment of roundness and circularity
We calculate the shape of the virus using the following descriptors: Circularity, aspect ratio (AR), Round (roundness), and Solidity (area/convex area). Comparing the roundness of a virus is another factor that may be a good indicator of quality. Roundness can be calculated mathematically using the following formula( \(Roundness=4\pi \times \text{a}\text{r}\text{e}\text{a}/\text{a}\text{r}\text{e}\text{a}/{\text{p}\text{e}\text{r}\text{i}\text{m}\text{e}\text{t}\text{e}\text{r}}^{2}\)). The roundness criteria describe how perfect the form of a virus is oval, ellipse, spherical, circular, and irregular. In addition, the study confirmed the findings of the loss function, which primarily focuses on surrounding protein projections that appeared in electron microscopy pictures as weighting about spherical physical shape, which seems in electron microscopy images as an approximately round polygon(Zhang and Yan 2020). Describe SARS-CoV 2 in situ using cryo-EM images are roughly spherical particles with varied sizes centered around 100 nm (Klein et al. 2020). The shape of the selected virus particle with spikes was measured using the “freehand selection” tool. The results of this analysis indicate the average round of SARS-CoV 2 and SARS-CoV was 89.90 nm and 91.65 nm sequentially, as shown in figure 8.
Maximal and minimal fitting ellipse and shape descriptors, such as aspect ratio and circularity, were determined. In figure 9, the black line represents the distribution circularity of the SARS-CoV and the red line for the SARS-CoV 2. A value of 1.0 indicates a perfect circle. The results show that the value approaches 0.0, an increasingly elongated, which would make the shape of both viruses non-circular.
4.3. Assessment of the Area size of virus.
TEM may be a vital technique for demonstrating viral infection, but it must be used with caution when interpreting cytoplasmic features to detect viral particles appropriately (Goldsmith et al. 2020),(Ogando et al. 2020). Electron microscopy can assist in the quick identification of viral illnesses since it can be conducted in a matter of hours. Analytical differences of morphological preservation attained by the various fixation and embedding procedures might explain the disparities in results. However, identify the source of the material and the patient's symptoms since they will lead to suggestions of prospective agents while ruling out others. The preparation technique is chosen based on the consistency of the sample, extraction, concentration, and tissue culture amplification. It must avoid false positives by distinguishing viruses from cell organelles or detritus, bacterial contamination (Miller 1986),(Kim et al. 2020). Hence, extracting the main characteristics of the Outside Shape Virus provides insight into its life cycle and how to reduce pandemic outbreaks. Our results have been remarkably close to those expected and showed that the average area size of SARS-CoV 2 and SARS-CoV are comparable in morphology and size, about 80%, based on the close taxonomic relatedness of the two viruses and the reports available on the virus. In addition, the SARS-C0V 2 has a broad shifting in the shape it, which proves improving Mutation Capabilities as shown in figure 10. Finally, Training the Artificial intelligence techniques required a database based on TEM morphology features can enable accelerated decision-making and improve understanding of how viruses spread. Furthermore, improved diagnostic tools and accuracy enabled new efficient therapeutic breakthroughs and identified most residents at risk as possibly having physiological traits (Alimadadi et al. 2020),(Alazab et al. 2020). In future work, we aim to integrate an optical sensor based on image processing by creating an algorithm model to identify and detect a virus in public spaces using TEM morphological features. Thus, that is the best answer to contain the pandemic and save doctors’ time(Taha et al. 2020), (Taha et al. 2021).