Methods: Colectomy samples were obtained from 11 adults (mean age 45.7, six males) who were residents of Northeastern Peninsular Malaysia. Microplastics were identified following chemical digestion of specimens and subsequent filtration. The samples were then examined for characteristics (abundance, length, shape, and color) and composition of three common polymer types using stereo- and Fourier Transform InfraRed (FTIR) microscopes.
Results: Microplastics were detected in all 11 specimens with an average of 331 particles/individual specimen or 28.1 ± 15.4 particles/g tissue. Filaments or fibers accounted for 96.1% of particles, and 73.1% of all filaments were transparent. Out of 40 random filaments from 10 specimens (one had indeterminate spectra patterns), 90% were polycarbonate, 50% were polyamide, and 40% were polypropylene.
Conclusion: Our study suggests that microplastics are ubiquitously present in the human colon.
METHODS: A literature search was conducted with the use of three online databases namely, Web of Science, Scopus, and ScienceDirect. Developed keywords strategy was used to include only the relevant articles. A Population Intervention Comparison Outcomes (PICO) strategy was used to develop the inclusion and exclusion criteria. Image quality was analyzed quantitatively based on peak signal-noise-ratio (PSNR), Mean Squared Error (MSE), Absolute Mean Brightness Error (AMBE), Entropy, and Contrast Improvement Index (CII) values.
RESULTS: Nine studies with four types of image enhancement techniques were included in this study. Two studies used histogram-based, three studies used frequency-based, one study used fuzzy-based and three studies used filter-based. All studies reported PSNR values whilst only four studies reported MSE, AMBE, Entropy and CII values. Filter-based was the highest PSNR values of 78.93, among other types. For MSE, AMBE, Entropy, and CII values, the highest were frequency-based (7.79), fuzzy-based (93.76), filter-based (7.92), and frequency-based (6.54) respectively.
CONCLUSION: In summary, image quality for each image enhancement technique is varied, especially for breast cancer detection. In this study, the frequency-based of Fast Discrete Curvelet Transform (FDCT) via the UnequiSpaced Fast Fourier Transform (USFFT) shows the most superior among other image enhancement techniques.