Extraction and visualization of structural information based on FDG-PET images

T. Tozaki, M. Senda
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引用次数: 2

Abstract

In this paper, we investigate the methods to express the structural information such as tube-like shape or isolated region based on fluoro-deoxy glucose(FDG) PET images and its visualization. To extract the human structural information, we calculate the curvatures of two types. One is calculated by Hessian matrix, the other is based on the four dimensional hyper-surface of FDG-PET images. There are three curvatures through each calculations, and these curvatures express original structures such as the linear shape and isolation degree. Using by these features, we extract the abnormal regions which include doubtful cancer. For the visualization, we propose to construct the newly image, that is the extracted abnormal regions are superimposed on the ordinary image which used for diagnosis of cancer. Moreover, we evaluate each abnormal regions from the view point such as the statistical FDG accumulation or the shape information, and we certify the effectiveness of out methods in the diagnosis of cancer.
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基于FDG-PET图像的结构信息提取与可视化
本文研究了基于氟脱氧葡萄糖(FDG) PET图像的管状或孤立区域等结构信息的表达方法及其可视化。为了提取人体结构信息,我们计算了两种类型的曲率。一种是基于Hessian矩阵计算,另一种是基于FDG-PET图像的四维超表面。通过每次计算得到三个曲率,这些曲率表示原始结构,如线性形状和隔离度。利用这些特征提取可疑癌变的异常区域。在可视化方面,我们提出构建新的图像,即将提取的异常区域叠加在用于癌症诊断的普通图像上。此外,我们还从FDG的统计累积量或形状信息等角度对每个异常区域进行了评价,验证了我们的方法在癌症诊断中的有效性。
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