ABSTRACT
The proposed work describes an approach for the segmentation of abnormal lung CT scans of COVID-19. Lung diseases are the leading killer in both men and women. The pulmonary experts normally make attempts, such as early detection of patients by tomography tests before lung specialists treat patients who are tortured by lung disease. Moreover, lung specialists do their best to detect the presence of lung conditions. X rays or CT scan checks are performed for tomography tests. The finest approach for medical diagnosis and a wide range of uses is computed tomography (CT). This kind of imaging offers elaborate cross-sectional pictures of skinny slices of the organic structure. However, the preprocessing and denoising methods of Lung CT scans may mask some important image features. To address this challenge, we propose a novel framework involving an optimization technique algorithm to solve a multilevel thresholding problem based on information theory to segment abnormal lung CT scans. The proposed framework will evaluate a sample of CT scan images taken from a well-known benchmark database. The evaluation results will assess subjectively and objectively to demonstrate the effectiveness of the proposed framework.
ABSTRACT
OBJECTIVE: The relevance of growth determination in orthodontics is driving the search for the most precise and least invasive way of tracking the pubertal growth spurt. Our aim was to explore whether minimally invasive salivary estimation of biomarkers Insulin-like growth factor (IGF-1) and Insulin-like growth factor binding protein-3 (IGFBP-3) could be used to estimate skeletal maturity for clinical convenience, especially in children and adolescent age groups. MATERIALS AND METHOD: The cross-sectional study was conducted on 90 participants (56 girls and 34 males) with ages ranging from 6 to 25 years. Each subject's hand-wrist radiograph was categorized based on skeletal maturity, and saliva samples were estimated for IGF-1 and IGFBP-3 using the respective ELISA kits. Kruskal-Wallis nonparametric ANOVA was applied to compare different skeletal stages. RESULTS: The study demonstrated low salivary IGF-1 levels at the prepubertal stage, with increase during pubertal onset and peak pubertal stage followed by a decline during pubertal deceleration to growth completion. Spearman's correlation coefficient demonstrated a strong positive association (r = 0.98 p < 0.01) between salivary IGF/IGFBP-3 ratio and different stages of skeletal maturity. CONCLUSION: Salivary IGF-1, IGFBP-3, and IGF/IGFBP-3 ratio could serve as a potential biochemical marker for predicting the completion of skeletal maturity.