基于内容医学图像检索的肺癌检测

Ritika Agarwal, Ankit Shankhadhar, R. Sagar
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引用次数: 24

摘要

本文对基于医学内容的图像检索检测肺癌的文献进行了综述。肺癌是一种突出的癌症,每年死亡人数超过100万。在计算机体层摄影医学图像中,需要对肺结节进行早期检测。因此,为了早期发现肿瘤结节的发生,对方法和技术的要求越来越高。虽然有不同的方法和技术,但没有一种能提供更好的检测精度。这提供了基于内容的图像检索计算机辅助诊断系统(CAD),用于从胸部计算机断层扫描(CT)图像中早期检测肺结节。在拟议的CAD系统中描述了不同的阶段。这包括从胸部计算机断层扫描(CT)图像中提取肺区域,分割肺区域,从分割区域提取特征,以及肺癌的发生和不发生的分类。本文介绍了现有的文献和用于检测肺癌的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Lung Cancer Using Content Based Medical Image Retrieval
This paper is a review of the literature on detection of lung cancer using medical content based image retrieval. Lung cancer is prominent cancer as it states large number of deaths of more than a million every year. It creates need of detecting the lung nodule at early stage in Computer Tomography medical images. So to detect the occurrence of cancer nodule at early stage, the requirement of methods and techniques is increasing. There are different methods and techniques existing but none of them provide a better accuracy of detection. This provides content based image retrieval Computer Aided Diagnosis System (CAD) for early detection of lung nodules from the Chest Computer Tomography (CT) images. There are various phases described in the proposed CAD system. These are extraction of lung region from chest computer tomography (CT) images, segmentation of the lung region, feature extraction from the segmented region, and the classification of occurrence and non-occurrence of cancer in the lung. This paper describes the available literature and the techniques used for the detection of lung cancer.
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