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FluoSA (Fluorescence Signal Analyzer)

 

FluoSA inputs *.LIF and *.tif files, detects user-defined neural structures, and quantifies the fluorescence signal changes (frame-wise fluorescence intensity and the dF/F0) in these structures.

 

The outputs of FluoSA include:

  1. An annotated video showing the detected neural structures:

    alt text

  2. Spreadsheets storing frame-wise fluorescence intensity in each detected neural structure:

    alt text

  3. Spreadsheets storing summary of fluorescence signal changes (dF/F0) in each detected neural structure:

    alt text

 

Installation

1 Install FluoSA

python3 -m pip install FluoSA

2 Install CUDA toolkit v11.8

https://developer.nvidia.com/cuda-11-8-0-download-archive?target_os=Windows&target_arch=x86_64

3 Install Detectron2

python3 -m pip install 'git+https://github.com/facebookresearch/detectron2.git'

4 Install PyTorch 2.0.1

4.1 For Windows and Linux

4.1.1 If using GPU
python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118
4.1.2 CPU only
python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cpu

4.2 For Mac

python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2

 

Usage

In your terminal / command prompt, type:

FluoSA

Then the user interface will be initiated:

alt text

Metadata

Release files for FluoSA 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for FluoSA 1.0.0
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fluosa-1.0.0.tar.gz 26.9 kB Details

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Table of built distributions (wheels) for FluoSA 1.0.0
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fluosa-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 58.5 kB

Release files / fluosa-1.0.0.tar.gz

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