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pyradiomics.html
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<!doctype html>
<html class="no-js" lang="en">
<head>
<title>Radiomics</title>
<meta name="description" content="Radiomics - quantitative radiographic phenotyping">
<meta name="keywords" content="">
<meta charset="utf-8">
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<h1 class="white-text">py-Radiomics</h1>
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<span class="white-text">Open-source radiomics library written in python</span>
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<a class="highlight-link-pyrad text-uppercase pubmed" target="_blank"
href="pyradiomicsnotebook.html">How it works</i></a>
<a class="highlight-link-pyrad text-uppercase pubmed" target="_blank"
href="http://pyradiomics.readthedocs.io/en/latest/installation.html">
   Install it   </a>
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<p class="wow fadeInUp ">Pyradiomics is an open-source python package for the extraction of radiomics data from medical images. Image loading and preprocessing (e.g. resampling and cropping) are first done using SimpleITK. Loaded data is then converted into numpy arrays for further calculation using multiple feature classes. Optional filters are also built-in.
<br><br>Pyradiomics has recently been accepted in Cancer Research.</p>
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<span class="title-small text-uppercase font-weight-700 white-text letter-spacing-1 margin-seven display-block">Open-source
</span>
<p class="margin-ten no-margin-top width-90 xs-center-col xs-display-block white-text">Pyradiomics is developed as an open-source library hosted on Github. We encourage people to contribute code, bugs and feature requests.</p>
<a href="https://github.com/Radiomics/pyradiomics" target="_blank" class="highlight-link text-uppercase black-text">GITHUB<i class="fa fa-long-arrow-right extra-small-icon black-text" ></i></a>
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</span>
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All installation instructions, methods and feature classes - together with the relevant mathematical formulae - are fully documented.
</p>
<a href="http://pyradiomics.readthedocs.io/en/latest/index.html" target="_blank" class="highlight-link text-uppercase black-text">DOCUMENTATION<i class="fa fa-long-arrow-right extra-small-icon black-text" ></i></a>
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<span class="title-small text-uppercase font-weight-700 white-text letter-spacing-1 margin-seven display-block">How it works</span>
<p class="margin-ten no-margin-top width-90 xs-center-col xs-display-block white-text">
Import the pyradiomics library into a Jupyter [ipython] notebook and extract selected features either from single images or in batch mode. </p>
<a href="pyradiomicsnotebook.html" target="_blank" class="highlight-link text-uppercase black-text">Jupyter notebook<i class="fa fa-long-arrow-right extra-small-icon black-text" ></i></a>
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<span class="title-small text-uppercase font-weight-700 white-text letter-spacing-1 margin-seven display-block">Community</span>
<p class="margin-ten no-margin-top width-90 xs-center-col xs-display-block white-text">
Browse the community Discourse forum for frequently asked questions regarding installation, usage and methods - or post your own. </p>
<a href="https://discourse.slicer.org/c/community/radiomics" target="_blank" class="highlight-link text-uppercase black-text">Radiomics Discourse Forum<i class="fa fa-long-arrow-right extra-small-icon black-text" ></i></a>
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<span class="title-med text-uppercase font-weight-500 black-text letter-spacing-1">PY-RADIOMICS VIDEO TUTORIAL<br><br></span>
<iframe width="560" height="315" src="https://www.youtube.com/embed/ZF1rTtRW3eQ" frameborder="0" allowfullscreen></iframe>
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<div class="spend-year wow fadeIn"><span>Commits</span>538</div>
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<h5>We'd love to help you with pyradiomics</h5>
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© 2017 Computational Imaging & Bioinformatics Lab - Harvard Medical School
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