Department of Computer Science, National Chiao Tung University, HsinChu, Taiwan.
PLoS Comput Biol. 2012;8(9):e1002658. doi: 10.1371/journal.pcbi.1002658. Epub 2012 Sep 13.
Drosophila melanogaster is a well-studied model organism, especially in the field of neurophysiology and neural circuits. The brain of the Drosophila is small but complex, and the image of a single neuron in the brain can be acquired using confocal microscopy. Analyzing the Drosophila brain is an ideal start to understanding the neural structure. The most fundamental task in studying the neural network of Drosophila is to reconstruct neuronal structures from image stacks. Although the fruit fly brain is small, it contains approximately 100,000 neurons. It is impossible to trace all the neurons manually. This study presents a high-throughput algorithm for reconstructing the neuronal structures from 3D image stacks collected by a laser scanning confocal microscope. The proposed method reconstructs the neuronal structure by applying the shortest path graph algorithm. The vertices in the graph are certain points on the 2D skeletons of the neuron in the slices. These points are close to the 3D centerlines of the neuron branches. The accuracy of the algorithm was verified using the DIADEM data set. This method has been adopted as part of the protocol of the FlyCircuit Database, and was successfully applied to process more than 16,000 neurons. This study also shows that further analysis based on the reconstruction results can be performed to gather more information on the neural network.
黑腹果蝇是一种研究得很好的模式生物，特别是在神经生理学和神经回路领域。果蝇的大脑很小但很复杂，使用共聚焦显微镜可以获得单个神经元的图像。分析果蝇大脑是理解神经网络的理想起点。研究果蝇神经网络的最基本任务是从图像堆栈中重建神经元结构。尽管果蝇的大脑很小，但它包含大约 100000 个神经元。不可能手动追踪所有的神经元。本研究提出了一种从激光扫描共聚焦显微镜采集的 3D 图像堆栈中重建神经元结构的高通量算法。该方法通过应用最短路径图算法来重建神经元结构。图中的顶点是切片中神经元 2D 骨架上的某些点。这些点靠近神经元分支的 3D 中心线。该算法的准确性已通过 DIADEM 数据集进行验证。该方法已被纳入 FlyCircuit 数据库的协议中，并成功应用于处理超过 16000 个神经元。本研究还表明，可以基于重建结果进行进一步分析，以收集更多有关神经网络的信息。
