CREMI

这一挑战的目标是评估从串行切片电子显微镜数据中自动重建神经元和神经元连接的算法。不仅通过评估神经元分割的质量，还通过评估检测突触和识别突触伙伴的准确性来进行比较。该挑战是在来自成年黑腹果蝇大脑组织的三个大型且多样化的数据集上进行的，包括神经元分割基础事实和突触连接的注释。一个成功的解决方案将证明其效率和普遍性，并具有巨大的潜力，可以减少在电子显微镜体积中手动重建神经回路所花费的时间。

The goal of this challenge is to evaluate algorithms for the automatic reconstruction of neurons and neuronal connections from serial section electron microscopy data. Comparisons will be conducted not only by assessing the quality of neuronal segmentation, but also by evaluating the accuracy of synapse detection and synaptic partner identification. This challenge is carried out on three large, diverse datasets derived from the brain tissue of adult Drosophila melanogaster, which include ground truth annotations for neuronal segmentation and synaptic connections. A successful solution will demonstrate its efficiency and generalizability, while holding great potential to reduce the time spent on manual neural circuit reconstruction from electron microscopy volumes.