• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Current Science: A Fortnightly Journal of Research >Automatic recognition of acute lymphoblastic leukemia using multi-SVM classifier
【24h】

Automatic recognition of acute lymphoblastic leukemia using multi-SVM classifier

机译：使用多SVM分类器自动识别急性淋巴细胞白血病

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

Acute lymphoblastic leukemia (ALL) is the most popular form of white blood cells cancer in children. It is classified into three forms of L1, L2 and L3. Typically, it is identified through screening of blood smearsvia pathologists. Since this is laborious and tedious, automatic systems are desired for suitable detection; but the high similarity between morphology of ALL forms and that of normal, reactive and a typical lymphocytes, makes the automatic detection a challenging problem. This study tried to improve the accuracy of detection based on principle component analysis (PCA). After segmenting nuclei of cells, numerous features were extracted. The first six components of this feature space were used for the binary and multiclass support vector machine classifiers. An expert pathologist was used to appraise this method as a gold standard. A collation with similar work indicated that using PCA instead of using exclusively selected features enhanced the average sensitivity and specificity of classification up to 10%. The results demonstrate that this algorithm performs better than similar studies. Its permissible efficiency for identifying ALL and its sub-types as well as other lymphocyte forms makes it an associate diagnostic device for pathologists.
机译：急性淋巴细胞白血病（全部）是儿童中最受欢迎的白细胞癌症形式。它被分为三种形式的L1，L2和L3。通常，通过筛选血液孢粉病理学家来鉴定它。由于这是艰苦而繁琐的，因此需要自动系统进行合适的检测;但是所有形式的形态与正常，反应性和典型淋巴细胞的形态之间的高相似性使自动检测有挑战性的问题。本研究试图提高基于原理成分分析（PCA）检测的准确性。在细胞分段细胞核后，提取了许多特征。此特征空间的前六个组件用于二进制和多字符支持向量机分类器。专家病理学家被用来评估这种方法作为黄金标准。与类似工作的整理表明，使用PCA而不是使用专门的特征，增强了高达10％的平均灵敏度和特异性。结果表明，该算法比类似的研究更好。其允许的效率识别所有及其子类型以及其他淋巴细胞形式，使其成为病理学家的助理诊断装置。

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