3D Neuron

3D neuron reconstruction aims to accurately model the complex three-dimensional structures of neurons from microscopy images, facilitating analysis of their morphology and function. Current research focuses on improving segmentation accuracy using deep learning approaches, including transformer-based models and generative adversarial networks (GANs), often leveraging pre-training on large natural image datasets to overcome data scarcity in neuroscience. These advancements are crucial for connectomics, enabling more precise mapping of neural circuits and ultimately furthering our understanding of brain function and neurological disorders.