• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Conference on Medical Imaging: Computer-Aided Diagnosis >Computer-aided prognosis of neuroblastoma: Classification of stromal development on whole-slide images
【24h】

Computer-aided prognosis of neuroblastoma: Classification of stromal development on whole-slide images

机译：神经母细胞瘤的计算机辅助预后：全幻灯片上的基质发育分类

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Neuroblastoma is a cancer of the nervous system and one of the most common tumors in children. In clinical practice, pathologists examine the haematoxylin and eosin (H&E) stained tissue slides under the microscope for the diagnosis. According to the International Neuroblastoma Classification System, neuroblastoma tumors are categorized into favorable and unfavorable histologies. The subsequent treatment planning is based on this classification. However, this qualitative evaluation is time consuming, prone to error and subject to inter- and intra-reader variations and sampling bias. To overcome these shortcomings, we are developing a computerized system for the quantitative analysis of neuroblastoma slides. In this study, we present a novel image analysis system to determine the degree of stromal development from digitized whole-slide neuroblastoma samples. The developed method uses a multi-resolution approach that works similar to how pathologists examine slides. Due to their very large resolutions, the whole-slide images are divided into non-overlapping image tiles and the proposed image analysis steps are applied to each image tile using a parallel computation infrastructure developed earlier by our group. The computerized system classifies image tiles as stroma-poor or stroma-rich subtypes using texture characteristics. The developed method has been independently tested on 20 whole-slide neuroblastoma slides and it has achieved 95% classification accuracy.
机译：神经母细胞瘤是神经系统的癌症和儿童中最常见的肿瘤之一。在临床实践中，病理学家在显微镜下检查血红素和曙红（H＆E）染色组织载玻片，用于诊断。根据国际神经母细胞瘤分类系统，神经母细胞瘤肿瘤被分类为有利和不利的组织学。随后的治疗规划是基于该分类。然而，这种定性评估是耗时的，容易出错并且受到读者间变异和采样偏差的影响。为了克服这些缺点，我们正在开发一种用于神经母细胞瘤载玻片的定量分析的计算机化系统。在本研究中，我们提出了一种新颖的图像分析系统，以确定数字化全载神经母细胞瘤样品的基质发育程度。开发方法使用多分析方法，该方法类似于病理学家如何检查幻灯片。由于它们非常大的分辨率，将整个滑动图像分成非重叠图像瓦片，并且所提出的图像分析步骤应用于每个图像块，使用我们组早先开发的并行计算基础设施。计算机化系统使用纹理特性将图像瓦片分类为基质差或富有的基质亚型。开发方法已在20种全载体神经母细胞瘤载玻片上独立测试，实现了95％的分类精度。

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