Skip to main content

Some scripts to register images in space and time

Project description

Registration tools

Purpose and "history"

This repository is about two scripts to do spatial and temporal registration of 3D microscopy images. It was initially developed to help friends with their ever moving embryos living under a microscope. I found that actually quite a few people were interested so I made a version of it that is somewhat easier to use.

In theory, the main difficulty to make the whole thing work is to install the different libraries.

Credits

The whole thing is just a wrapping of the amazing blockmatching algorithm developed by S. Ourselin et al. and currently maintained Grégoire Malandin et al.@Team Morpheme - inria (if I am not mistaking).

Installation

conda and pip are required to install registration-tools

We recommand to install the registration tools in a specific environement (like conda). For example the following way:

conda create -n registration python=3.10

You can then activate the environement the following way:

conda activate registration

For here onward we assume that you are running the commands from the registration conda environement.

Then, to install the whole thing, it is necessary to first install blockmatching. To do so you can run the following command:

conda install vt -c morpheme

Then, you can install the 3D-registration library either directly via pip:

pip install 3D-registration

Or, if you want the latest version, by specifying the git repository:

pip install git+https://github.com/GuignardLab/registration-tools.git

Troubleshooting

  • Windows:

    If you are trying to run the script on Windows you might need to install pthreadvse2.dll.

    It can be found there: https://www.pconlife.com/viewfileinfo/pthreadvse2-dll/ . Make sure to download the version that matches your operating system (32 or 64 bits, most likely 64).

Usage

Most of the description on how to use the two scripts is described in the manual (Note that the installation part is quite outdated, the remaining is ok).

That being said, once installed, one can run either of the scripts from anywhere in a terminal by typing:

time-registration

or

spatial-registration

The location of the json files or folder containing the json files will be prompted and when provided the registration will start.

It is also possible to run the registration from a script/notebook the following way:

from registrationtools import TimeRegistration
tr = TimeRegistration('path/to/param.json')
tr.run_trsf()

or

from registrationtools import TimeRegistration
tr = TimeRegistration('path/to/folder/with/jsonfiles/')
tr.run_trsf()

or

from registrationtools import TimeRegistration
tr = TimeRegistration()
tr.run_trsf()

and a path will be asked to be inputed.

Example json files

Few example json files are provided to help the potential users. You can find informations about what they do in the manual.

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

3d_registration-0.5.4.tar.gz (211.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

3d_registration-0.5.4-py3-none-any.whl (219.4 kB view details)

Uploaded Python 3

File details

Details for the file 3d_registration-0.5.4.tar.gz.

File metadata

  • Download URL: 3d_registration-0.5.4.tar.gz
  • Upload date:
  • Size: 211.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.5

File hashes

Hashes for 3d_registration-0.5.4.tar.gz
Algorithm Hash digest
SHA256 650dd8c891c496f494f5845c48e6741655b7bb64ac5368cb7e88d50759251c02
MD5 ed1a4cdc97c19f25252d50761a56ee6b
BLAKE2b-256 bbee881f4670355b036aada95bfb4e9d0b49132f5f37be18051694a8d9db863e

See more details on using hashes here.

File details

Details for the file 3d_registration-0.5.4-py3-none-any.whl.

File metadata

File hashes

Hashes for 3d_registration-0.5.4-py3-none-any.whl
Algorithm Hash digest
SHA256 522e940417df72ae494ae6db4e97d0b61f4b29dd756022baf45cce17c5b4c6d7
MD5 5678f774bcf6a1b9fe96b626f9d3ad29
BLAKE2b-256 8921b433070b6ac7f92a585ece1121a8a7edf6aff2ee0fbe143a61122ea7f72b

See more details on using hashes here.

Supported by

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