Thickness Profile

Thickness profile analysis focuses on accurately determining the thickness of structures across various fields, from medical imaging to materials science, aiming to extract meaningful information from this spatial variation. Current research employs diverse approaches, including Gaussian mixture models for line thickness estimation, attention-based deep learning for interpolating CT scan slices to improve segmentation accuracy, and deep learning-based registration methods for faster cortical thickness estimation in brain imaging. These advancements improve the precision and efficiency of thickness measurements, impacting fields like medical diagnosis (e.g., detecting neurodegenerative diseases), materials characterization (e.g., thin film analysis), and engineering (e.g., structural analysis of plates).