Microscopic Image

Microscopic image analysis focuses on extracting meaningful information from images obtained through microscopes, primarily aiming for automated and accurate classification, segmentation, and feature extraction. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), transformers, and autoencoders, often enhanced with attention mechanisms and domain adaptation techniques to address challenges like limited data and variations in imaging conditions. This field is crucial for accelerating diagnoses in medicine (e.g., cancer detection, malaria diagnosis), advancing materials science (e.g., characterizing nanomaterials), and improving efficiency in other domains like archaeology and environmental monitoring.