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Nodule detection from posterior and anterior chest radio graph using circular hough transform

机译:使用环形霍夫变换从胸部前后影像学检查结节

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摘要

Lung cancer is the foremost cause of death in many regions of the world. Early detection betters the chances of survival. PA chest radiography is the most commonly used diagnosis tool for detecting lung tumor, because it is cost effective and requires less radiation dose. Radiologists fail to detect nodule from PA chest radio graphs, at early stage because of complex anatomical structure present in radio graphs. Computer aided diagnosis systems are developed to assist radiologist in detecting tumor from radio graphs at early stage. Paper describes the algorithms to find potential nodule from Posterior and Anterior (PA) chest radio graphic images. In this paper two algorithms were proposed to detect tumor from PA chest radio graphs. In the first method tumor is separated from radio graphic image using different techniques like threshold, region growing and morphological operations and identified using geometrical features extracted from the segmented tumor. In second method tumor detected automatically with threshold and Circular Hough transform.
机译:在世界许多地区,肺癌是最主要的死亡原因。早期发现可提高生存机会。 PA胸部X射线照相术是检测肺部肿瘤最常用的诊断工具,因为它具有成本效益并且需要较少的放射线剂量。由于放射线图中存在复杂的解剖结构,放射科医生在早期无法从PA胸部放射线图中检测到结节。开发了计算机辅助诊断系统,以协助放射科医生在早期从放射线图检测肿瘤。论文描述了从胸部前后图像(PA)中寻找潜在结节的算法。在本文中,提出了两种从PA胸部放射线图检测肿瘤的算法。在第一种方法中,使用不同的技术(例如阈值,区域生长和形态学操作)将肿瘤与放射线图像分离,并使用从分段肿瘤中提取的几何特征进行识别。在第二种方法中,使用阈值和圆霍夫变换自动检测肿瘤。

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