https://vilab.team/author/%E7%94%98%E9%B2%81%E6%96%8C/ 甘鲁斌 Hugo Blox Builder (https://hugoblox.com)en-usMon, 27 Oct 2025 00:00:00 +0000 https://vilab.team/author/%E7%94%98%E9%B2%81%E6%96%8C/avatar_hu2272367383815033900.jpg https://vilab.team/author/%E7%94%98%E9%B2%81%E6%96%8C/ 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-expert-systems-with-applications-130161/ Mon, 27 Oct 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-expert-systems-with-applications-130161/ <p>热烈祝贺甘鲁斌同学！论文《Enhancing zero-shot brain tumor subtype classification via fine-grained patch-text alignment》已发表在 <em>Expert Systems with Applications</em> 130161。</p> <h2 id="enhancing-zero-shot-brain-tumor-subtype-classification-via-fine-grained-patch-text-alignment">Enhancing zero-shot brain tumor subtype classification via fine-grained patch-text alignment</h2> <p><strong>祝贺甘鲁斌同学！该论文已发表在 <em>Expert Systems with Applications</em> 130161。</strong></p> <p> <figure > <div class="d-flex justify-content-center"> <div class="w-100" ><img alt="Enhancing zero-shot brain tumor subtype classification via fine-grained patch-text alignment" 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-expert-systems-with-applications-130161/images/paper-01_hu479104807647607719.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-expert-systems-with-applications-130161/images/paper-01_hu7525044382441938419.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-expert-systems-with-applications-130161/images/paper-01_hu10830315984298057718.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-expert-systems-with-applications-130161/images/paper-01_hu479104807647607719.webp" width="760" height="445" loading="lazy" data-zoomable /></div> </div></figure> </p> <ul> <li><strong>作者：</strong> Lubin Gan、Jing Zhang、Linhao Qu、Yijun Wang、Siying Wu、Xiaoyan Sun</li> <li><strong>发表载体：</strong> <em>Expert Systems with Applications</em> 130161</li> <li><strong>发表时间：</strong> 2025年10月27日</li> <li><strong>相关链接：</strong> <a href="https://www.sciencedirect.com/science/article/pii/S0957417425037765" target="_blank" rel="noopener">论文链接</a> · <a href="https://arxiv.org/pdf/2508.01602" target="_blank" rel="noopener">PDF</a></li> </ul> <h3 id="论文介绍">论文介绍</h3> <p>本文提出细粒度补丁对齐网络（FG-PAN），用于脑肿瘤亚型的零样本分类。该方法包含局部特征细化模块，通过建模代表性补丁间的空间关系增强视觉特征；以及细粒度文本描述生成模块，利用大语言模型生成病理感知的类别语义原型。通过对齐细粒度视觉与语义特征，并引入坐标感知聚合机制，FG-PAN在整张病理切片级别实现了更准确的亚型判别，缓解了标注数据稀缺和形态差异细微带来的挑战。</p>