Situ Hybridization

In situ hybridization (ISH) is a powerful technique for visualizing gene expression within cells and tissues, but analyzing the resulting images is often laborious and subjective. Current research focuses on automating ISH image analysis using deep learning methods, particularly convolutional neural networks (CNNs) and autoencoders, to improve accuracy, speed, and objectivity. These automated pipelines incorporate image registration techniques, often employing implicit neural representations or shape-based approaches to align images from different sources or with varying expression patterns. This automation promises to accelerate biological discovery and improve diagnostic accuracy in fields like oncology and microbiology.