https://vilab.team/author/%E5%BC%A0%E5%93%B2%E5%AE%87/ 张哲宇 Hugo Blox Builder (https://hugoblox.com)en-usTue, 10 Jun 2025 00:00:00 +0000 https://vilab.team/author/%E5%BC%A0%E5%93%B2%E5%AE%87/avatar_hu2898067775315891118.jpg https://vilab.team/author/%E5%BC%A0%E5%93%B2%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-cvpr/ Tue, 10 Jun 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-cvpr/ <p>热烈祝贺张哲宇同学！论文《Incomplete multi-modal brain tumor segmentation via learnable sorting state space model》已发表在 <em>CVPR</em>。</p> <h2 id="incomplete-multi-modal-brain-tumor-segmentation-via-learnable-sorting-state-space-model">Incomplete multi-modal brain tumor segmentation via learnable sorting state space model</h2> <p><strong>祝贺张哲宇同学！该论文已发表在 <em>CVPR</em>。</strong></p> <p> <figure > <div class="d-flex justify-content-center"> <div class="w-100" ><img alt="Incomplete multi-modal brain tumor segmentation via learnable sorting state space model" srcset=" /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-cvpr/images/paper-01_hu12446196012194697519.webp 400w, /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-cvpr/images/paper-01_hu11624591397241064252.webp 760w, /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-cvpr/images/paper-01_hu8784721236978794445.webp 1200w" src="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-cvpr/images/paper-01_hu12446196012194697519.webp" width="760" height="210" loading="lazy" data-zoomable /></div> </div></figure> </p> <ul> <li><strong>作者：</strong> Zheyu Zhang、Yayuan Lu、Feipeng Ma、Yueyi Zhang、Huanjing Yue、Xiaoyan Sun</li> <li><strong>发表载体：</strong> <em>CVPR</em></li> <li><strong>发表时间：</strong> 2025年6月10日</li> <li><strong>相关链接：</strong> <a href="https://ieeexplore.ieee.org/abstract/document/11094296/" target="_blank" rel="noopener">论文链接</a> · <a href="https://openaccess.thecvf.com/content/CVPR2025/papers/Zhang_Incomplete_Multi-modal_Brain_Tumor_Segmentation_via_Learnable_Sorting_State_Space_CVPR_2025_paper.pdf" target="_blank" rel="noopener">PDF</a></li> </ul> <h3 id="论文介绍">论文介绍</h3> <p>本文提出一种可学习排序状态空间模型（LS3M），用于不完整多模态脑肿瘤分割。该方法基于Mamba架构高效建模长距离依赖，并引入可微置换矩阵，根据模态特定特征对输入序列进行动态重排序，从而保留3D脑MRI中关键的空间归纳偏置与长程语义相关性。LS3M能够充分利用可用模态信息，提升分割性能。</p>