A retinal blood vessel extraction algorithm based on CART decision tree and improved AdaBoost

This paper presents a supervised learning algorithm for retinal vascular segmentation based on classification and regression tree（CART） algorithm and improved adptive bosting（AdaBoost）. Local binary patterns（LBP） texture features and local features are extracted by extracting, reversing, dilating an...

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Hlavní autoři:	DIWU Peng-peng, HU Ya-qi
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Publishing Center of North University of China 2019-01-01
Edice:	Journal of Measurement Science and Instrumentation
Témata:	classification and regression tree（CART） improved adptive boosting（AdaBoost） retinal blood vessel local binary pattern（LBP） texture
On-line přístup:	http://jmsi.publish.founderss.cn/thesisDetails?columnId=47038618&Fpath=home&index=0
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