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INTELLECTUAL METHOD OF DIAGNOSTICS AND DETECTION OF NEOPLASMS IN LUNGS

机译:诊断方法和肿块中恶性肿瘤的检测方法

摘要

FIELD: medicine.;SUBSTANCE: invention relates to medicine, namely to the diagnosis of lung cancer. Method comprises the processing of images of the patient's lungs obtained by computed tomography, as a result of which voxels with density values according to the Hounsfield scale that do not correspond to the density values of the lung tissue are masked in the graphic image; subsequent segmentation of voxels located on the surface of the "candidates" of the neoplasms; construction of a set of chords formed by combinations of pairs of points located in the allocated voxels on the surface of the "candidates" of the neoplasms; the construction of a histogram of the distribution of the length of the chords with the reduction to the maximum length of the chord constructed within the boundaries of each "candidate" of the neoplasm; the formation of a feature vector including the data of the constructed histogram of the distribution of chord lengths, average value of density according to the Hounsfield scale of each "candidate" of the neoplasm, the total number of voxels in each "candidate" of the neoplasm. After that, according to the formed vector of characteristics, each candidate "candidate" of neoplasms is classified as a true malignant neoplasm using the machine learning algorithm that implements the functions of the classifier.;EFFECT: invention provides a reduction in the number of detected false positive neoplasms in the lungs.;1 cl, 5 dwg
机译:技术领域本发明涉及医学,即肺癌的诊断。该方法包括处理通过计算机断层摄影术获得的患者肺部的图像,其结果是在图形图像中掩盖了具有根据霍恩斯菲尔德标度的密度值的不对应于肺组织密度值的体素;随后分割位于肿瘤“候选”表面的体素;构造一组和弦,这些和弦由位于肿瘤“候选”表面上分配的体素中的成对的点对组合而成;在各个肿瘤“候选”的边界内,构造和弦长度分布的直方图,并减小到所构造的和弦的最大长度;特征向量的形成,包括构造的弦长分布直方图的数据,根据肿瘤的每个“候选”的Hounsfield尺度的密度平均值,每个“候选”的体素总数肿瘤。之后,根据形成的特征向量,使用实现分类器功能的机器学习算法,将每个候选肿瘤“候选”分类为真正的恶性肿瘤。效果:本发明减少了检测到的数量肺中的假阳性肿瘤; 1 cl,5 dwg

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