迈向核医学中详细的全身群分析

N. Ferreira, F. Caramelo, A. Liborio, M. Botelho, S. Carvalho, L. Mendes, R. Faustino, M. Ribeiro, A. Rodrigues
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引用次数: 3

摘要

在本文中,我们描述了一个目前正在进行的项目。我们指出了项目的关键思想,解释了所选方法的优点和缺点。拥有影像设备的诊所每年会产生大量的信息,但大多数情况下,这些信息没有得到充分利用,因为检查是单独分析的,没有对个体进行比较,也没有对特定人群的特征进行探索。在这些情况下,数据挖掘是可取的,但是图像数据库很难分析,因为它们依赖于鲁棒和自动的分割和分类方法。提出了一种基于分类方法的核医学图像(全身PET扫描)分割方法。分割的区域也被标记并用作结构化数据库的附加特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards detailed whole body group analysis in nuclear medicine
In this work we describe a project that is currently in progress. We point out the key ideas of the project explaining the pros and cons of the chosen approach. A clinic with image facilities produces a huge amount of information per year that, most of the times, is underused since exams are analyzed individually without the comparison between individuals or the exploration of features of a certain population. Data mining would be recommendable in these cases, however image databases are difficult to analyze because they depend on robust and automatic methods of segmentation and classification. We propose a method for segmenting nuclear medicine images (whole body PET scans) based on a classification method. The segmented regions are also labeled and used as additional features for a structured database.
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