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Three-dimensional CT image retrieval in a database for classification between benign and malignant pulmonary nodules

机译:在数据库中进行三维CT图像检索以对肺结节进行良恶性分类

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This paper aims at obtaining diagnosis and prognosis information by searching similar images into a three-dimensional (3-D) CT image database of pulmonary nodules for which diagnosis is known. For this purpose, we propose an automatic method to retrieve nodule candidates with similar characteristics from the database. Each pulmonary nodule image is represented by the distribution pattern of CT density and 3-D curvature index. The nodule representation is then applied to a similarity measure such as a correlation coefficient. Our database is composed of 263 pulmonary nodules with associated clinical information. For each new case, we sort all the nodules of the database from most to less similar ones. By applying the retrieval method to our database, we present its feasibility to search the similar 3-D nodule images.
机译:本文旨在通过将相似的图像搜索到已知诊断的肺结节的三维(3-D)CT图像数据库中,从而获得诊断和预后信息。为此,我们提出了一种自动方法,可以从数据库中检索具有相似特征的候选结核。每个肺结节图像均由CT密度和3-D曲率指数的分布模式表示。然后将结节表示应用于相似性度量,例如相关系数。我们的数据库由263个肺结节和相关的临床信息组成。对于每个新案例,我们将数据库中的所有结节从大多数到不太相似的地方进行排序。通过将检索方法应用于我们的数据库,我们提出了搜索相似的3D结节图像的可行性。

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