Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.
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Updated
Dec 13, 2024 - Python
Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.
Complete Matlab pipeline for large scale calcium imaging data analysis
Matlab routines for online non-rigid motion correction of calcium imaging data
Calibrated inference of spiking from calcium ΔF/F data using deep networks
CIAtah (pronounced cheetah): a software package for calcium imaging analysis of one- and two-photon imaging datasets. Documentation: https://git.io/ciatah_docs. Formerly known as calciumImagingAnalysis (ciapkg).
Accurate denoising of voltage imaging data through statistically unbiased prediction, Nature Methods.
High level pandas-based API for batch analysis of Calcium Imaging data using CaImAn
Platform for Calcium Imaging analysis. DEPRECATED.
A table containing imaging analysis tools for biology, with a focus on calcium imaging.
a Python machine learning library for neurophysiology data
Fast, Simple Calcium Imaging Segmentation with Fully Convolutional Networks (https://arxiv.org/abs/1707.06314)
Seeded Iterative Demixing (SID) of neuronal activity recordings made using Light Field Microscopy (LFM)
Flow-Registration toolbox for 2P motion compensation
SamuROI - Structured analysis of multiple user-defined ROIs, an open source Python-based analysis environment for imaging data.
Official code for BEAR. "Efficient neural network approximation of robust PCA for automated analysis of calcium imaging data", MICCAI 2021.
Real-time, interactive exploration of 3D image stacks
HNCcorr algorithm for neuron identification in calcium imaging datasets.
Bonsai package for controlling headborne, calcium imaging miniscopes
This repository contains code for morphology-free analysis of functional fluorescence microscopy. The focal algorithm, Graph-Filtered Time-trace (GraFT) Dictionary Learning, is published in Charles et al. 2022 in the IEEE Transactions of Image Processing.
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