https://vilab.team/author/%E7%8E%8B%E6%B5%A9%E5%AE%87/ 王浩宇 Hugo Blox Builder (https://hugoblox.com)en-usThu, 28 Aug 2025 00:00:00 +0000 https://vilab.team/author/%E7%8E%8B%E6%B5%A9%E5%AE%87/avatar_hu5926457529337530769.jpg https://vilab.team/author/%E7%8E%8B%E6%B5%A9%E5%AE%87/ https://vilab.team/event/%E7%A5%9D%E8%B4%BA%E5%AE%9E%E9%AA%8C%E5%AE%A4%E7%A7%91%E7%A0%94%E6%88%90%E6%9E%9C%E5%8F%91%E8%A1%A8%E4%BA%8E-artificial-intelligence-in-medicine/ Thu, 28 Aug 2025 00:00:00 +0000 https://vilab.team/event/%E7%A5%9D%E8%B4%BA%E5%AE%9E%E9%AA%8C%E5%AE%A4%E7%A7%91%E7%A0%94%E6%88%90%E6%9E%9C%E5%8F%91%E8%A1%A8%E4%BA%8E-artificial-intelligence-in-medicine/ <p>热烈祝贺王浩宇同学！论文《MMSupcon: An image fusion-based multi-modal supervised contrastive method for brain tumor diagnosis》已发表在 <em>Artificial Intelligence in Medicine</em>。</p> <h2 id="mmsupcon-an-image-fusion-based-multi-modal-supervised-contrastive-method-for-brain-tumor-diagnosis">MMSupcon: An image fusion-based multi-modal supervised contrastive method for brain tumor diagnosis</h2> <p><strong>祝贺王浩宇同学！该论文已发表在 <em>Artificial Intelligence in Medicine</em>。</strong></p> <ul> <li><strong>作者：</strong> Haoyu Wang、Jing Zhang、Siying Wu、Haoran Wei、Xun Chen、Yunwei Ou、Xiaoyan Sun</li> <li><strong>发表载体：</strong> <em>Artificial Intelligence in Medicine</em></li> <li><strong>发表时间：</strong> 2025年8月28日</li> <li><strong>相关链接：</strong> <a href="https://www.sciencedirect.com/science/article/pii/S0933365725001885" target="_blank" rel="noopener">论文链接</a></li> </ul> <h3 id="论文介绍">论文介绍</h3> <p>本文针对脑肿瘤多模态MRI诊断中融合策略受限于样本稀缺的问题，提出多模态监督对比学习方法MMSupcon。该方法通过多模态医学图像融合生成信息丰富的样本，并设计多模态监督对比损失，引导模型有效整合互补模态信息，提升诊断准确性。</p>