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Fractal Dimension Image Processing for Feature Extraction and Morphological Analysis: Gd3+/13X/Dox/Fa Mri Nanocomposite Publisher



Ghaderi S1
Authors
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Authors Affiliations
  1. 1. Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran

Source: Journal of Nanomaterials Published:2023


Abstract

One of the most fundamental subjects in nanoscience and nanotechnology is structural analysis. We employed a scanning electron microscope (SEM) image of the manufactured Gd3+/13X/DOX/FA nanocomposite in this study. The size, dimensions, and morphology of nanocomposite materials were studied to ensure the uniformity and homogeneity of SEM images. This is the first study to look at segmented SEM images for fractal dimension (FD) and other statistical criteria, including average, maximum, minimum, skewness, and range for magnetic resonance imaging (MRI) nanocomposite. The average of FD (FDavg), the standard deviation of FD (FDsd), and the lacunarity of FD (FDlac) fractal data analysis criteria were also employed. The findings show that particle sizes and shapes vary because the minimum-to-maximum range is not zero, and our data provide a reasonable range. This interpretation is further supported by an analysis of the nanocomposite's SEM image. At first glance, the image seemed to be uniform. However, when the calculations were performed, it was discovered that the generated particles were not particularly uniform. The particles were uniformly dispersed throughout all surfaces, although their sizes, dimensions, and morphologies varied. In conclusion, the study was supported by fractal data analysis, emphasizing the importance of structural analysis for future research, particularly for medical applications like MRI. © 2023 Sadegh Ghaderi.