Skip to main content

Registration package that does affine and LDDMM registration

Project description

# ndreg [![Travis](https://travis-ci.org/neurodata/ndreg.svg?branch=master)](https://travis-ci.org/#) [![Documentation Status](https://readthedocs.org/projects/ndreg/badge/?version=latest)](http://ndreg.readthedocs.io/en/latest/?badge=latest) [![DockerHub](https://img.shields.io/docker/pulls/neurodata/ndreg.svg)](https://hub.docker.com/r/neurodata/ndreg) <br/> Package that performs affine and LDDMM registration easily <br/>

## Sytem Requirements

The recommended way to use this package is to install [Docker](https://store.docker.com/search?offering=community&type=edition). Docker is currently available on Mac OS X El Capitan 10.11 and newer macOS releases, the following Ubuntu versions: Zesty 17.04 (LTS), Yakkety 16.10, Xenial 16.04 (LTS), Trusty 14.04 (LTS), and Windows 10.

### Software Dependencies (with version numbers)

The only software dependency needed if using the recommended method is Docker. The following dependencies are included in the Docker Image.

External libraries: <br/> - Insight Segmentation and Registration Toolkit (ITK) – 4.12.2

Python depedencies: <br/> - jupyter – (1.0.0) - numpy – (1.13.3) - scikit-image – (0.13.1) - scikit-learn – (0.19.1) - scipy – (1.0.0) - SimpleITK – (1.0.1)

### Versions tested on We have tested the Docker image and build on macOS High Sierra (on MacBook Pro with 2.9 GHz Intel Core i7 and 16 GB RAM) and Ubuntu Xenial 16.04.3 LTS (with 64 GB RAM).

## Installation Guide

Once Docker is installed on your machine, pull the neurodata/ndreg image from Docker Hub [here](https://hub.docker.com/r/neurodata/ndreg) as follows: <br/>

docker pull neurodata/ndreg <br/>

It will typically take around 3 minutes to pull the entire Docker image.

## Demo

### Instructions to run on data

In order to use the functionality built into this Docker image, you need to run the Docker image:

docker run -p 8888:8888 neurodata/ndreg <br/>

This should print a link to the terminal console that looks like this: <br/>

http://0.0.0.0:8888/?token=SOME_TOKEN <br/>

Go to this link in your browser by copying and pasting it. <br/>

Next, click on ndreg_demo.ipynb. Once the notebook opens, you can run all cells by clicking on ‘Cell’ and then ‘Run All’.

The expected run time for this demo is ~ 2 minutes.

### Expected Output

The last 3 cells in the demo notebook display images that should look the same (both the LDDMM registered image and the displacement field warped image) and a mean squared error

### Congrats, you’ve succesfully run ndreg!

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

ndreg-1.0.0.tar.gz (18.5 kB view details)

Uploaded Source

Built Distribution

ndreg-1.0.0-cp27-cp27m-macosx_10_13_intel.whl (18.2 kB view details)

Uploaded CPython 2.7m macOS 10.13+ intel

File details

Details for the file ndreg-1.0.0.tar.gz.

File metadata

  • Download URL: ndreg-1.0.0.tar.gz
  • Upload date:
  • Size: 18.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for ndreg-1.0.0.tar.gz
Algorithm Hash digest
SHA256 1ea5388cb1d25be9cb57f43fd009300382870de1c26cd3e64764f8fcf73b1214
MD5 7c5ef0c8bf02abec9a6ceeb31849b993
BLAKE2b-256 15f3740e4e37b89341bfca6c7fc7753eae4e64f7207540b500d60cc742250705

See more details on using hashes here.

File details

Details for the file ndreg-1.0.0-cp27-cp27m-macosx_10_13_intel.whl.

File metadata

File hashes

Hashes for ndreg-1.0.0-cp27-cp27m-macosx_10_13_intel.whl
Algorithm Hash digest
SHA256 b4bac5c82a1d06b5e0a7b31f23a72fb3257602fc3c6af92323efeca4aea71275
MD5 aa6acb3203a920c98dce1a39c0a8ede9
BLAKE2b-256 12f657778729ba40123e17c24e892a4fbdab00be57885a559966dfc4c8f95841

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