Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Scientific vocabulary similarity
Low similarity (12.4%) to scientific vocabulary
Repository
Image Processing package for large, 3D (volumetric) image data
Basic Info
- Host: GitHub
- Owner: aecon
- License: mit
- Language: Python
- Default Branch: main
- Size: 541 KB
Statistics
- Stars: 6
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
img3D
img3 is a python package for image processing of large, 3D (volumetric) image data.
img3 is intended for: * storing NumPy arrays in raw file format * storing and reading image metadata from corresponding nrrd files, used in bio-imaging * perform copmutations on image data
Code Structure
The img3D package is organized as follows: * src : Source (C and Python) files. * examples : Examples of simple use cases of the package.
Requirements
- C compiler
- numpy
Optional requirements
- C compiler with OpenMP support
- ImageJ
- Python packages: tifffile, numba, scipy.signal
Compilation
cd src
make install
To customize the python interpreter, C compiler, and the compilation flags:
cd src
make install PY=python CC=clang CFLAGS_OPENMP= 'CFLAGS = -O2 -g'
Applications
Below are results from projects where img3D modules were used.
A project-specific pipeline was developed to process and generate the quantification needed for each project.
The rendering of the generated 3D segmentations was performed with Paraview.
Project 1: Image processing for the quantification of drug efficacy
A study for the efficacy of different drugs in neurodegenerative diseases.
A novel image processing pipeline utilizing img3D modules was developed to quantify drug efficacy on the sub-cellular level, through object segmentation of stained neural cells in 3D whole mouse-brain scans.
The pipeline will be published together with the corresponding publication.
Project 2: Quantification of drug bio-distribution through 3D image processing
An international collaboration aiming to develop a new protein-based delivery system to the central nervous system of the brain.
3D images of whole mouse-brain scans were used to detect the bio-distribution of the delivery system, using light-sheet microscopy.
Image processing was performed using a custom pipeline utilizing img3D modules.
Paper currently under review in Cell. The pipeline will be published together with the corresponding publication.
Authors
The package was developed in the labs of Prof. Petros Koumoutsakos (ETH Zurich) and Prof. Adriano Aguzzi (University of Zurich) by * Sergey Litvinov * Athena Economides * Francesca Catto
Owner
- Name: Athena Economides
- Login: aecon
- Kind: user
- Location: Zurich
- Company: ETH Zürich
- Repositories: 1
- Profile: https://github.com/aecon
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Litvinov
given-names: Sergey
orcid:
- family-names: Economides
given-names: Athena
orcid:
- family-names: Catto
given-names: Francesca
orcid:
- family-names: Aguzzi
given-names: Adriano
orcid:
- family-names: Koumoutsakos
given-names: Petros
orcid:
title: "img3D: An Image Processing library for large 3D image data."
version: 1.0.0
doi:
date-released: