<?xml version="1.0" encoding="utf-8" standalone="yes" ?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Zihan Yan | ViLab</title>
    <link>https://vilab.team/author/zihan-yan/</link>
      <atom:link href="https://vilab.team/author/zihan-yan/index.xml" rel="self" type="application/rss+xml" />
    <description>Zihan Yan</description>
    <generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 08 Jul 2024 00:00:00 +0000</lastBuildDate>
    <image>
      <url>https://vilab.team/media/icon_hu2896232876136423579.png</url>
      <title>Zihan Yan</title>
      <link>https://vilab.team/author/zihan-yan/</link>
    </image>
    
    <item>
      <title>Advancing presurgical non-invasive molecular subgroup prediction in medulloblastoma using artificial intelligence and MRI signatures</title>
      <link>https://vilab.team/publication/advancing-presurgical-non-invasive-molecular-subgroup-predic/</link>
      <pubDate>Mon, 08 Jul 2024 00:00:00 +0000</pubDate>
      <guid>https://vilab.team/publication/advancing-presurgical-non-invasive-molecular-subgroup-predic/</guid>
      <description>&lt;p&gt;本文构建了涵盖中国和美国13个中心934例髓母细胞瘤患者的国际分子特征数据库，利用人工智能和MRI影像特征实现术前无创的分子亚型预测。通过交叉验证、外部验证和连续验证，证明了模型作为通用分子诊断分类器的有效性，并通过对MRI特征的详细分析，从影像学角度深化了对髓母细胞瘤的理解，为临床管理提供了低成本、可推广的替代路径。&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Eoformer: Edge-oriented transformer for brain tumor segmentation</title>
      <link>https://vilab.team/publication/eoformer-edge-oriented-transformer-for-brain-tumor-segmentat/</link>
      <pubDate>Sun, 01 Oct 2023 00:00:00 +0000</pubDate>
      <guid>https://vilab.team/publication/eoformer-edge-oriented-transformer-for-brain-tumor-segmentat/</guid>
      <description>&lt;p&gt;本文提出边缘导向Transformer（EoFormer），用于脑肿瘤MRI图像分割。该方法采用CNN-Transformer混合编码器，CNN提取局部低级特征，Transformer建模长距离依赖以生成全局高级特征；解码器集成边缘导向Sobel与Laplacian锐化模块，增强边缘信息。同时引入高效注意力与重参数化技术，提升特征表示能力与分割精度。&lt;/p&gt;
</description>
    </item>
    
  </channel>
</rss>
