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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>MedCoDi-M: Multimodal Medical Data Generation</title>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0-beta3/css/all.min.css">
<style>
body {
font-family: Arial, sans-serif;
margin: 0;
padding: 0;
background-color: #f9f9f9;
color: #333;
}
.container {
max-width: 800px;
margin: 50px auto;
text-align: center;
}
h1 {
font-size: 2.5em;
margin-bottom: 20px;
}
p {
line-height: 1.6;
font-size: 1.1em;
}
img {
max-width: 100%;
height: auto;
margin: 20px 0;
}
.buttons {
margin: 30px 0;
}
.button {
text-decoration: none;
background-color: #007bff;
color: white;
padding: 10px 20px;
border-radius: 5px;
font-size: 1.1em;
margin: 5px;
display: inline-block;
}
.button:hover {
background-color: #0056b3;
}
</style>
</head>
<body>
<div class="container text-center">
<h1>MedCoDi-M: A Multi-Prompt Foundation Model for Multimodal Medical Data Generation</h1>
<div class="authors">
<strong>Daniele Molino</strong>, <strong>Paolo Soda</strong>, <strong>Valerio Guarrasi</strong>
</div>
<div class="affiliations">
<p>Research Unit of Computer Systems and Bioinformatics, Department of Engineering, Università Campus Bio-Medico di Roma, Roma, Italy, Europe.</p>
<p>Department of Diagnostics and Intervention, Radiation Physics, Biomedical Engineering, Umeå University, Umeå, Sweden, Europe.</p>
</div>
<div class="buttons">
<a href="#" class="button" style="background-color: gray; cursor: not-allowed;"><i class="fas fa-file-alt"></i> Paper (Coming Soon)</a>
<a href="https://huggingface.co/spaces/dmolino/MedCoDi-M" class="button"><i class="fas fa-vial"></i> Demo on HuggingFace</a>
<a href="https://github.com/danielemolino/MedCoDi-M" class="button"><i class="fab fa-github"></i> GitHub Repository</a>
</div>
<img src="Model.png" alt="MedCoDi-M Model Diagram">
<!-- Abstract. -->
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Abstract</h2>
<div class="content has-text-justified">
<p>
MedCoDi-M is an innovative multimodal framework for medical data generation. By leveraging contrastive learning and modular training, it facilitates any-to-any generation across medical data modalities, effectively tackling challenges related to data scarcity, privacy preservation, and multimodal integration.
</p>
</div>
</div>
</div>
</div>
</body>
</html>