基于恶性概率计算和肺CT扫描图像自动分割的肺癌早期诊断

S. Manoharan, A. Sathesh
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引用次数: 61

摘要

建立了计算机辅助检测系统,对肺结节进行识别以诊断癌细胞。本研究的主要目的是通过数据和CPU基础设施实现自动图像分析和恶性肿瘤计算。该算法采用改进滤波器对输入图像进行增强和对结节进行选择,采用神经分类器进行误检。该模型在内、外两种结核中进行了试验,所得结果以响应特性曲线表示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Early diagnosis of Lung Cancer with Probability of Malignancy Calculation and Automatic Segmentation of Lung CT scan Images
Computer aided detection system was developed to identify the pulmonary nodules to diagnose the cancer cells. Main aim of this research enables an automated image analysis and malignancy calculation through data and CPU infrastructure. Our proposed algorithm has improvement filter to enhance the imported images and for nodule selection and neural classifier for false reduction. The proposed model is experimented in both internal and external nodules and the obtained results are shown as response characteristics curves.
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