Lung Nodule Detection and Classification using Random Forest: A Review

Nada S. El-Askary, M. A. Salem, Mohamed Roushdy
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引用次数: 1

Abstract

Lung nodule is an abnormal growth of tissues in the lung that can be an onset for lung cancer. Fast detection for those nodules and classifying them will ensure better chances for treatments. Random Forest (RF) is a powerful machine learning algorithm and a state-of-the-art technology that proved to give rewarding results in helping radiologies diagnosing lung pathologies. The paper presents a survey on recent researches made for lung nodule detection and classification using RF. Wide range of datasets can be used for lung nodule detection are listed. Different models with the used features and their results are discussed in this review.
基于随机森林的肺结节检测与分类综述
肺结节是肺组织的异常生长,可能是肺癌的前兆。对这些结节的快速检测和分类将确保更好的治疗机会。随机森林(RF)是一种强大的机器学习算法,也是一种最先进的技术,在帮助放射学诊断肺部病变方面得到了有益的结果。本文综述了近年来射频在肺结节检测与分类中的研究进展。列出了可用于肺结节检测的广泛数据集。本文讨论了不同的模型及其所使用的特征和结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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