CN113408603B - 一种基于多分类器融合的冠状动脉狭窄病变程度识别方法 - Google Patents
一种基于多分类器融合的冠状动脉狭窄病变程度识别方法 Download PDFInfo
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CN110490040A (zh) * | 2019-05-30 | 2019-11-22 | 浙江理工大学 | 一种识别dsa冠状动脉图像中局部血管狭窄程度的方法 |
CN111667456A (zh) * | 2020-04-28 | 2020-09-15 | 北京理工大学 | 一种冠状动脉x光序列造影中血管狭窄检测方法及装置 |
CN112184647A (zh) * | 2020-09-22 | 2021-01-05 | 清华大学深圳国际研究生院 | 基于迁移卷积网络对眼底图像进行血管病变分级识别方法 |
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US10055551B2 (en) * | 2013-10-10 | 2018-08-21 | Board Of Regents Of The University Of Texas System | Systems and methods for quantitative analysis of histopathology images using multiclassifier ensemble schemes |
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CN103489005A (zh) * | 2013-09-30 | 2014-01-01 | 河海大学 | 一种基于多分类器融合的高分辨率遥感影像分类方法 |
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CN108108762A (zh) * | 2017-12-22 | 2018-06-01 | 北京工业大学 | 一种用于冠心病数据分类的基于核极限学习机及并行化的随机森林分类方法 |
CN108805858A (zh) * | 2018-04-10 | 2018-11-13 | 燕山大学 | 基于数据挖掘的肝病ct图像计算机辅助诊断***及方法 |
CN110490040A (zh) * | 2019-05-30 | 2019-11-22 | 浙江理工大学 | 一种识别dsa冠状动脉图像中局部血管狭窄程度的方法 |
WO2021081771A1 (zh) * | 2019-10-29 | 2021-05-06 | 未艾医疗技术(深圳)有限公司 | 基于vrds ai医学影像的心脏冠脉的分析方法和相关装置 |
CN111667456A (zh) * | 2020-04-28 | 2020-09-15 | 北京理工大学 | 一种冠状动脉x光序列造影中血管狭窄检测方法及装置 |
CN112184647A (zh) * | 2020-09-22 | 2021-01-05 | 清华大学深圳国际研究生院 | 基于迁移卷积网络对眼底图像进行血管病变分级识别方法 |
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