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index.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="theme-color" content="#68ACC6">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
<title>Medical Imaging & Deep Learning</title>
<link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet">
<link href="./assets/css/main.css" rel="stylesheet">
<link href="./assets/css/index.css" rel="stylesheet">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js"></script>
<script src="./assets/js/custom/main.js"></script>
<!-- Global site tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=G-QD6MB5R106"></script>
<script>
window.dataLayer = window.dataLayer || [];
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gtag('js', new Date());
gtag('config', 'G-QD6MB5R106');
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</head>
<body>
<div id="top_menu"></div>
<div id="hero">
<div class="row flex-md-row-reverse align-items-center g-5 py-5">
<div class="d-flex col-12 col-lg-6 img-container justify-content-center">
<img src="./assets/imgs/hero.png" class="d-block mx-lg-auto img-fluid" width="500" height="500" loading="lazy">
</div>
<div class="col-lg-6 padding-left-lg">
<h1 class="display-5 fw-bold lh-1 mb-3" style="color:#FFF">MIDeL —<br>Medical Image Deep Learning</h1>
<p class="lead mb-5">
MIDeL is a website to help healthcare professionals and medical imaging scientists learn to apply deep learning methods to medical images. This website consists of a comprehensive text (think of an electronic textbook) combined with actual code examples to help you learn about Deep Learning.
</p>
<div class="d-flex justify-content-center">
<a class="btn btn-lg col-8 col-md-6 shadow" href="./chapters.html" role="button">Get Started Now!</a>
</div>
</div>
</div>
</div>
<div class="container">
<div class="row justify-content-center">
<div class="col col-12 col-md-9 fs-5 text-center mb-5">
We specifically focus on the MONAI framework, as it provides many nice functions that work well with medical images. This means that you will need to use Python and the PyTorch framework. If that sounds intimidating don't worry – the first few chapters provide background on programming, as well as the math and medical image fundamentals that some of you may lack. If you know this already great – feel free to skip forward to the chapters where you encounter material that you are not familiar with...
</div>
</div>
<div class="row card-container">
<div class="col col-12 offset-sm-0 offset-md-1 offset-lg-2 col-md-5 col-lg-4 mb-3 d-flex align-items-stretch">
<div class="card shadow p-2">
<div class="card-body">
<img src="./assets/icons/text-icon.png" class="mb-2" style="width: 45px;">
<h5 class="card-title mb-4" style="color:#71A9B1">Comprehensive Text</h5>
<p class="card-text">MIDeL provides a comprehensive text covering everything from medical image properties, math for DL, but focuses intensely on Deep Learning for medical imaging.</p>
</div>
</div>
</div>
<div class="col col-12 col-md-5 col-lg-4 mb-3 d-flex align-items-stretch">
<div class="card shadow p-2">
<div class="card-body">
<img src="./assets/icons/code-icon.png" class="mb-2" style="width: 45px;">
<h5 class="card-title mb-4" style="color:#71A9B1">Working Code Examples</h5>
<p class="card-text">For each chapter in the text, there is a corresponding IPython/Jupyter Notebook code base, which can be downloaded from GitHub, and executed on a public website like Colab or your own server.</p>
</div>
</div>
</div>
</div>
</div>
<footer class="col-12 text-center bg-light text-muted mt-5"></footer>
</body>
</html>