flatironinstitute/CaImAn

Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.

What it solves

CaImAn is a Python toolbox designed for the large-scale analysis of calcium and voltage imaging data. It addresses the challenge of processing high-volume fluorescence microscopy data to extract meaningful biological signals from noise and motion artifacts.

How it works

The toolbox implements a suite of scalable algorithms to process imaging data. It handles motion correction to stabilize images, source extraction to identify neurons, spike deconvolution to estimate neural activity, and registration to track neurons across different recording sessions. It supports both one-photon and two-photon fluorescence microscopy and can operate in either offline (post-processing) or online (real-time) modes.

Who it’s for

Researchers in neuroscience and biological imaging who need to process large-scale calcium or voltage imaging datasets to identify neural activity patterns.

Highlights

  • Versatile Imaging Support: Works with both one-photon and two-photon fluorescence microscopy data.
  • Scalable Algorithms: Provides fast methods for motion correction, source extraction, and spike deconvolution.
  • Real-time Capability: Supports online analysis modes (e.g., OnACID) for real-time experiments.
  • Multi-session Tracking: Includes tools to register neurons across multiple imaging sessions.
  • Comprehensive Demos: Offers a wide range of Jupyter notebooks covering use cases from 3D volumetric imaging to dendritic analysis.

Related

  • Project
    MouseLand/suite2p

    A processing pipeline for two-photon calcium imaging data that extracts large-scale neural activity through registration, ROI detection, and spike detection.

  • Project
    brainiak/brainiak

    A Python-based analysis kit for neuroscience research, focusing on the processing and analysis of functional Magnetic Resonance Imaging (fMRI) data.

  • Project
    scikit-image/scikit-image

    scikit-image is a Python library for image processing that provides a collection of algorithms for analyzing and manipulating images.

  • Project
    rapidsai/cucim

    cuCIM is a GPU-accelerated computer vision and image processing library designed for large, multidimensional images used in biomedical, geospatial, and remote sensing applications.

  • Project
    InsightSoftwareConsortium/ITK

    An open-source, cross-platform toolkit for N-dimensional scientific image processing, segmentation, and registration, primarily used for medical image analysis.