Skip to main content

A Python-based GUI for Histological E-data Registration in Brain Space

Project description

HERBS

A Python-based GUI for Histological E-data Registration in Brain Space

HERBS is an open source, extensible, intuitive and interactive software platform for image visualisation and image registration. Where the image registration is the process of identifying a spatial transformation that maps images to a template such that corresponding anatomical structures are optimally aligned, or in other words, a voxel-wise ‘correspondence’ is established between the images and template.

HERBS has been tested on Windows 10, MacOSx (Big Sur - Monterey), Linux (Kubuntu 18.04, Ubuntu 22.04 LTS), and as a python application, it should run in all environments supporting python 3.8.10-3.10.4 / 3.9.0 with PyQt5 >= 5.14.2 as a GUI framework. For details, please see HERBS CookBook (on going).

HERBS provides users:

  • 2D and 3D visualisation of brain atlas volume data and arbitrary slicing.
  • Image registration with interactive local elastic deformation methods in current version.
  • 2D and 3D visualisation of user defined data.

Install

$ pip install herbs

Please install the newest version of HERBS.

Usage

import herbs
herbs.run_herbs()

After running the above scripts, a GUI window will pop up. Users can download atlas and upload images for further process,

For more information, please read HERBS CookBook (on going) or check the Tutorial folder for corresponding functionalities.

Some Pre-Requirement Issues

  • In order to run HERBS properly, 64 bit operating systems and 64 bit Python are required.

  • 3D visualisation in HERBS depends on OpenGL, if you face to the problem that no OpenGL is installed on your machine, please see (https://www.opengl.org) to download and install accordingly.

  • For the current version of HERBS, Python is required to be installed. Please see (https://www.python.org) for downloading.

  • If you would like to install HERBS through terminal, pip is required.

    • Check if pip is installed, pip --version or pip help.
    • Use python3 -m ensurepip for MacOS to install pip.
    • Use curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py to download requiring file for installing pip on Windows and python get-pip.py to install pip.
    • Please update pip to the newest version before installing HERBS.
  • We strongly recommend users to use Python and install packages with virtual environment. For no-coders, we strongly recommend to use IDE to create environment at the moment. A desktop app of HERBS is coming soon.

Some Dependencies Conflict Issues

  • The initial of test of HERBS was carried on Windows 10 (one user claimed he had a Windows 11 before, but it turned out to be a Windows 10 at the end), MacOSx (Big Sur - Monterey) and Linux (Kubuntu 18.04, Ubuntu 22.04 LTS) with Python==3.8.10 and the corresponding dependencies listed in CookBook.

  • The current tests showed that different version of Python accepts different versions of dependencies. For example, PyQt5 == 5.14.2 works when Python>=3.8.10, PyQt5 >= 5.15.0 works when Python==3.9 and PyQt5 >= 5.15.5 works when Python==3.10 on a Windows 10.

  • HERBS depends on Numba and the valid version for Numba is highly depends on the version of Numpy. For example, Numba == 0.54 only works when Numpy <= 1.20 and Numba == 0.55 only works when Numpy <= 1.21 and so on.

  • If you face to these kinds of problems, the easiest way to install HERBS is to create a new environment and install HERBS without previous installation of any dependencies.

Please report your issues: https://github.com/JingyiGF/HERBS/issues. Please have a good description (maybe a screenshot or an error message). Any feedback welcome!

Please feel free to start any discussion: https://github.com/JingyiGF/HERBS/discussions.

Finally

HERBS is 'always' in development, please check updates every time before you use it.

Hope this tool makes your amazing research life more tasty :-)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

herbs-0.0.16.tar.gz (320.6 kB view details)

Uploaded Source

Built Distribution

herbs-0.0.16-py3-none-any.whl (396.0 kB view details)

Uploaded Python 3

File details

Details for the file herbs-0.0.16.tar.gz.

File metadata

  • Download URL: herbs-0.0.16.tar.gz
  • Upload date:
  • Size: 320.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for herbs-0.0.16.tar.gz
Algorithm Hash digest
SHA256 9c73e5ade36159b0e5f92a8190512967911e7bdeecb46b8886ee95d2fda0de29
MD5 e4feccb3c5b972cbeb01391ab59e4ae9
BLAKE2b-256 6bfb512ff68530d7b1503587bba345c6933fe76574fe40fbfc604b5a6478cd73

See more details on using hashes here.

File details

Details for the file herbs-0.0.16-py3-none-any.whl.

File metadata

  • Download URL: herbs-0.0.16-py3-none-any.whl
  • Upload date:
  • Size: 396.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for herbs-0.0.16-py3-none-any.whl
Algorithm Hash digest
SHA256 9a8c3af96a32e44a8b8ad38e1166d56e834024be860521d0f15732ea34d30695
MD5 eaee67e4e8cad2d621fa0cf688088430
BLAKE2b-256 5f55688f49edcf705018555c59de592375f2ed772f25ef38e11a8dba2b9088da

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page