基于图像处理的ct扫描图像特征提取方法

Anil K. Bharodiya
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引用次数: 1

摘要

医学图像处理涵盖了各种类型的图像,如断层摄影、乳房x光摄影、x射线摄影(x射线图像)、心电图、CT扫描图像等。一旦CT扫描图像被捕获,医生诊断它,以检测捕获的患者身体的异常或正常状况。在计算机图像处理诊断中,ct扫描图像要经历采集、图像增强、重要特征提取、感兴趣区域识别、结果解释等复杂阶段。在这些阶段中,特征提取阶段在自动/计算机图像处理过程中起着至关重要的作用,可以从ct扫描图像中检测ROI。该阶段执行科学、数学和统计操作/算法,从ct扫描图像中识别特征/特征,以缩小图像部分以进行诊断。在本章中,我对基于人体ct扫描图像的数字图像处理中的“特征提取”步骤进行了广泛的综述。
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Feature Extraction Methods for CT-Scan Images Using Image Processing
Medical image processing covers various types of images such as tomography, mammography, radiography (X-Ray images), cardiogram, CT scan images etc. Once the CT scan image is captured, Doctors diagnose it to detect abnormal or normal condition of the captured of the patient’s body. In the computerized image processing diagnosis, CT-scan image goes through sophisticated phases viz., acquisition, image enhancement, extraction of important features, Region of Interest (ROI) identification, result interpretation etc. Out of these phases, a feature extraction phase plays a vital role during automated/computerized image processing to detect ROI from CT-scan image. This phase performs scientific, mathematical and statistical operations/algorithms to identify features/characteristics from the CT-scan image to shrink image portion for diagnosis. In this chapter, I have presented an extensive review on “Feature Extraction” step of digital image processing based on CT-scan image of human being.
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