Dendrite Core

Dendrite core identification and segmentation are crucial tasks across diverse fields, from materials science to neuroscience, aiming to accurately locate the central point or delineate the entire structure of dendrites within complex 3D datasets. Current research employs advanced deep learning techniques, such as 3D convolutional neural networks (including U-Net and FCDenseNet architectures) and novel approaches like Frenet-frame-based segmentation, to improve the accuracy and efficiency of this process, particularly for challenging curvilinear structures. These advancements enable faster and more objective analysis of dendritic morphology, leading to improved understanding of material properties and biological processes, such as brain connectivity. The development of large, publicly available datasets further accelerates progress in this area.