Particle Picking

Particle picking, the automated identification and isolation of individual particles within microscopy images, is crucial for various scientific applications, including 3D protein structure determination and analysis of cloud particle properties. Current research focuses on leveraging machine learning, particularly neural networks and advanced segmentation models like the Segment Anything Model (SAM), to improve accuracy and efficiency, often addressing challenges like incomplete data, low contrast, and image artifacts through techniques such as prompt-based learning and neural style transfer. These advancements significantly reduce manual effort and improve the reliability of downstream analyses, impacting fields ranging from structural biology to atmospheric science.