The qim3d (kɪm θriː diː ) library is designed for Quantitative Imaging in 3D using Python. It offers a range of features, including data loading and manipulation, image processing and filtering, data visualization, and analysis of imaging results.

You can easily load and process 3D image data from various file formats, apply filters and transformations to the data, visualize the results using interactive plots and 3D volumetric rendering.

Whether you are working with medical imaging data, materials science data, or any other type of 3D imaging data, qim3d provides a convenient and powerful set of tools to help you analyze and understand your data.

Interactive volume slicer

import qim3d

vol = qim3d.examples.bone_128x128x128
qim3d.viz.slicer(vol)

Synthetic data generation

import qim3d

# Generate synthetic collection of blobs
num_objects = 15
synthetic_collection, labels = qim3d.generate.collection(num_objects = num_objects)

# Visualize synthetic collection
qim3d.viz.vol(synthetic_collection)

Structure tensor

import qim3d

vol = qim3d.examples.NT_128x128x128
val, vec = qim3d.processing.structure_tensor(vol, visualize = True, axis = 2)

Installation

Create environment

Creating a conda environment is not required but recommended.

Miniconda installation and setup

Miniconda is a free minimal installer for conda.

Here are some quick instructions to help you set up the latest Miniconda installer for your system:

WindowsmacOSLinux

The easiest way to install Miniconda on Windows is through the graphical interface installer. Follow these steps:

1. Download the installer here.
2. Run the installer and follow the on-screen instructions.
3. When the installation finishes, open Anaconda Prompt (miniconda3) from the Start menu.

The easiest way to install Miniconda on macOS is through the graphical interface installer. Follow these steps:

1. Download the correct installer for your processor version. If you are unsure about your version, check here.

   • For Intel processors, download x86
   • For Apple Silicon (M1/M2/M3 etc) processors, download arm64

2. Run the installer and follow the on-screen instructions.

These four commands quickly and quietly install the latest 64-bit version of the installer and then clean up after themselves. To install a different version or architecture of Miniconda for Linux, change the name of the .sh installer in the wget command.

mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm -rf ~/miniconda3/miniconda.sh

After installing, initialize your newly-installed Miniconda. The following commands initialize for bash and zsh shells:

~/miniconda3/bin/conda init bash
~/miniconda3/bin/conda init zsh

Once you have conda installed, open your terminal and create a new enviroment:

conda create -n qim3d python=3.11

After the environment is created, activate it by running:

conda activate qim3d

Remember, if you chose to create an environment to install qim3d, it needs to be activated each time before using the library.

Install using pip

The latest stable version can be simply installed using pip. Open your terminal and run:

pip install qim3d

Note

The base installation of qim3d does not include deep-learning dependencies, keeping the library lighter for scenarios where they are unnecessary. If you need to use deep-learning features, you can install the additional dependencies by running: pip install qim3d['deep-learning']

Troubleshooting

Here are some solutions for commonly found issues during installation and usage of qim3d.

Failed building

Some Windows users could face an build error during installation.

ERROR: Failed building wheel for noise

Building wheels for collected packages: noise, outputformat, asciitree, ffmpy
Building wheel for noise (setup.py) ... error
error: subprocess-exited-with-error

× python setup.py bdist_wheel did not run successfully.
│ exit code: 1
╰─> [14 lines of output]
    running bdist_wheel
    running build
    running build_py
    creating build
    creating build\lib.win-amd64-cpython-311
    creating build\lib.win-amd64-cpython-311\noise
    copying perlin.py -> build\lib.win-amd64-cpython-311\noise
    copying shader.py -> build\lib.win-amd64-cpython-311\noise
    copying shader_noise.py -> build\lib.win-amd64-cpython-311\noise
    copying test.py -> build\lib.win-amd64-cpython-311\noise
    copying __init__.py -> build\lib.win-amd64-cpython-311\noise
    running build_ext
    building 'noise._simplex' extension
    error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/
    [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for noise

This issue occurs because the system lacks the necessary tools to compile the library requirements. To resolve this, follow these steps:

• Go to the Visual C++ Build Tools page and click on "Download build tools."
• Run the installer and ensure that Desktop development with C++ is checked.
• Restart your computer
• Activate your conda enviroment and run pip install qim3d again

Get the latest version

The library is under constant development, so make sure to keep your installation updated:

pip install --upgrade qim3d

Collaboration

Contributions to qim3d are welcome!

If you find a bug, have a feature request, or would like to contribute code, please open an issue or submit a pull request.

You can find us at Gitlab: https://lab.compute.dtu.dk/QIM/tools/qim3d

This project is licensed under the MIT License.

Contributors

Below is a list of contributors to the project, arranged in chronological order of their first commit to the repository:

Author	Commits	First commit
Felipe Delestro	231	2023-05-12
Stefan Engelmann Jensen	29	2023-06-29
Oskar Kristoffersen	15	2023-07-05
Christian Kento Rasmussen	22	2024-02-01
Alessia Saccardo	13	2024-02-19
David Grundfest	16	2024-04-12
Anna Bøgevang Ekner	6	2024-04-18
David Diamond Wang Johansen	1	2024-10-31

Support

The development of qim3d is supported by: