...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Medical Imaging >Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging
【24h】

Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging

机译：歧管嵌入和语义分割用于高光谱脑成像术中指导

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Recent advances in hyperspectral imaging have made it a promising solution for intra-operative tissue characterization, with the advantages of being non-contact, non-ionizing, and non-invasive. Working with hyperspectral images in vivo, however, is not straightforward as the high dimensionality of the data makes real-time processing challenging. In this paper, a novel dimensionality reduction scheme and a new processing pipeline are introduced to obtain a detailed tumor classification map for intra-operative margin definition during brain surgery. However, existing approaches to dimensionality reduction based on manifold embedding can be time consuming and may not guarantee a consistent result, thus hindering final tissue classification. The proposed framework aims to overcome these problems through a process divided into two steps: dimensionality reduction based on an extension of the T-distributed stochastic neighbor approach is first performed and then a semantic segmentation technique is applied to the embedded results by using a Semantic Texton Forest for tissue classification. Detailed in vivo validation of the proposed method has been performed to demonstrate the potential clinical value of the system.
机译：高光谱成像的最新进展使其成为术中组织表征的有前途的解决方案，具有非接触，非电离和非侵入性的优势。但是，在体内处理高光谱图像并不是一件容易的事，因为数据的高维度使实时处理具有挑战性。本文介绍了一种新的降维方案和一条新的处理流程，以获取详细的肿瘤分类图，以进行脑部手术中术中切缘的定义。然而，现有的基于歧管嵌入的降维方法可能很耗时，并且可能无法保证结果的一致性，从而阻碍了最终的组织分类。所提出的框架旨在通过分为两个步骤的过程来克服这些问题：首先执行基于T分布随机邻居方法扩展的降维，然后使用语义Texton对嵌入的结果应用语义分割技术。森林组织分类。已对拟议方法进行了详细的体内验证，以证明该系统的潜在临床价值。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号