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A new approach for lung cancer cell detection using Mumford-shah algorithm

机译:Mumford-Shah算法的一种新方法肺癌细胞检测

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For detecting pleural effusion and pneumothorax, which affect the pleural membranes of the lungs, Computer Aided Diagnosis system (CAD) is proposed. The chest CT slices are initially preprocessed to remove the Gaussian noise by using a sigma filter segmentation technique used here extracts the lungs and the regions affected by pleural effusion using conventional thresholding techniques like Otsu's and iterative thresholding, followed by morphological operations. Mumford shah model is then applied, to segment the lung parenchyma as well as to extract the Region of Interest (ROI). Texture features are next extracted using Spectral texture extraction method from the ROIs, which are used to compute the feature vectors. These are used to train using multi-level slice classifier.
机译:为了检测影响肺的胸膜膜的胸腔积液和气胸,提出了计算机辅助诊断系统(CAD)。最初预处理的胸部CT切片通过使用这里使用的SIGMA滤波器分割技术来除去高斯噪声,使用诸如OTSU和迭代阈值相似的常规阈值的技术,然后使用迭代阈值阈值处理,然后进行形态操作。然后施用Mumford Shah模型,分段肺实质,并提取利益区域(ROI)。接下来使用来自ROI的光谱纹理提取方法提取纹理特征,用于计算特征向量。这些用于使用多级切片分类器训练。

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