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

Dr. T. Satyasavithri, Hyderabad, S. Devi, J. Duryea, J. Boone, E. Pietka, M. Brown, L. Wilson, B. Doust, R. Gill, Changming Sun
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引用次数: 2

Abstract

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.
利用圆形霍夫变换检测胸片前后位结节
肺癌是世界许多地区的首要死亡原因。早期发现会增加存活的机会。PA胸部x线摄影是检测肺部肿瘤最常用的诊断工具,因为它具有成本效益和较少的辐射剂量。由于胸片上复杂的解剖结构,放射科医生在早期无法从胸片上发现结节。计算机辅助诊断系统的开发是为了帮助放射科医生在早期阶段从放射图中发现肿瘤。本文介绍了从胸部后、前位放射图像中寻找潜在结节的算法。本文提出了两种从PA胸片中检测肿瘤的算法。第一种方法采用阈值、区域生长和形态学等技术将肿瘤从放射图像中分离出来,并利用分割后的肿瘤提取的几何特征进行识别。第二种方法采用阈值法和圆形霍夫变换对肿瘤进行自动检测。
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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