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InstantTrace: fast parallel neuron tracing on GPUs
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AI
DOI：10.1007/s00371-023-02969-w.png)
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Abstract
En 中文
Neuron tracing, also known as neuron reconstruction, is an essential step in investigating the morphology of neuronal circuits and mechanisms of the brain. Since the ultra-high throughput of optical microscopy (OM) imaging leads to images of multiple gigabytes or even terabytes, it takes tens of hours for the state-of-the-art methods to generate a neuron reconstruction from a whole mouse brain OM image. We introduce InstantTrace, a novel framework that utilizes parallel neuron tracing on GPUs, achieving a significant speed boost of more than 20x compared to state-of-the-art methods with comparable reconstruction quality on the BigNeuron dataset. Our framework utilizes two methods to achieve this performance advance. Firstly, it takes advantage of the sparse feature and tree structure of the neuron image, which serial tracing methods cannot fully exploit. Secondly, all stages of the neuron tracing pipeline, including the initial reconstruction stage that have not been parallelized in the past, are executed on GPU using carefully designed parallel algorithms. Furthermore, to investigate the applicability and robustness of the InstantTrace framework, a test on a whole mouse brain OM Image is conducted, and a preliminary neuron reconstruction of the whole brain is finished within 1 h on a singleGPU, an order of magnitude faster than the existing methods. Our framework has the potential to significantly improve the efficiency of the neuron tracing process, allowing neuron image experts to obtain a preliminary reconstruction result instantly before engaging in manual verification and refinement.
Keywords:
Neuron tracing
Neuron visualization
Image processing
GPU acceleration