2025/01/01 by Aeini, Ali
Biochemistry, Genetics and Molecular Biology · Engineering · Computer Science · #Cell Image Analysis Techniques #Image Processing Techniques and Applications #Medical Image Segmentation Techniques
paper · doi:10.17605/osf.io/mqnza
This project investigates the problem of trust and interpretability in microscopic and nanoscopic imaging. At small spatial scales, images are shaped not only by physical structures, but by wave phenomena, noise, and computational reconstruction processes, making visual plausibility an unreliable indicator of truth. The project proposes a theoretical calibration framework based on the use of micro- and nano-scale structures with precisely defined properties as perceptual reference patterns. These structures are not intended for instrument calibration, but for systematic comparison between known physical configurations and reconstructed images, allowing the identification of interpretation limits and artifact-prone regimes. The objective is not to reconstruct microscopic reality, but to constrain what can be reliably inferred from microscopic observations. The framework is modality-independent and aims to provide a principled basis for assessing confidence in image-based conclusions across microscopy, materials science, and biomedical imaging.