用Gabor滤波和支持向量机鉴别正常胸片和肺水肿胸片

Atul Kumar, Yen-Yu Wang, Kai-Che Liu, I-Chen Tsai, Ching-Chun Huang, Nguyen Hung
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引用次数: 14

摘要

肺水肿,即肺血管外液体过多,是各种临床疾病的常见表现。虽然肺水肿的病因是通过病史、体格检查和各种生化和放射学检查推断出来的,但肺水肿的计算机辅助评估将有助于医生确定病情的治疗过程。在这项研究中,我们提出了胸片的纹理分析,使用Gabor滤波和机器学习技术之一的支持向量机(SVM)来区分正常的胸片和肺水肿的胸片。这是利用胸部x线对肺水肿进行计算机辅助定量评估的第一步。
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Distinguishing normal and pulmonary edema chest x-ray using Gabor filter and SVM
Pulmonary edema, i.e. excess of extravascular fluid in lungs, is a common manifestation of various clinical conditions. Although the etiology of the pulmonary edema is deduced with the help of history, physical examination and various biochemical and radiological investigations, computer aided evaluation of pulmonary edema will be helpful for physicians in determining the course of management for the condition. In this study we present texture analysis of chest x-ray, using Gabor filter and one of the machine learning techniques, Support Vector Machine (SVM), to distinguish the normal chest x-ray from the chest x-ray of pulmonary edema. This is an initial step towards computer aided quantitative assessment of the pulmonary edema using chest x-ray.
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