BrainLine: An Open Pipeline for Connectivity Analysis of Heterogeneous Whole-Brain Fluorescence Volumes.
Thomas L AtheyMatthew A WrightMarija PavlovicVikram ChandrashekharKarl DeisserothMichael I MillerJoshua T VogelsteinPublished in: bioRxiv : the preprint server for biology (2023)
Whole-brain fluorescence images require several stages of computational processing to fully reveal the neuron morphology and connectivity information they contain. However, these computational tools are rarely part of an integrated pipeline. Here we present BrainLine, an open-source pipeline that interfaces with existing software to provide registration, axon segmentation, soma detection, visualization and analysis of results. By implementing a feedback based training paradigm with BrainLine, we were able to use a single learning algorithm to accurately process a diverse set of whole-brain images generated by light-sheet microscopy. BrainLine is available as part of our Python package brainlit: http://brainlit.neurodata.io/ .
Keyphrases
- resting state
- white matter
- functional connectivity
- deep learning
- convolutional neural network
- single molecule
- optical coherence tomography
- machine learning
- multiple sclerosis
- cerebral ischemia
- high resolution
- label free
- energy transfer
- single cell
- brain injury
- virtual reality
- quantum dots
- subarachnoid hemorrhage
- data analysis