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Moddicom:一个完整且易于访问的、依赖图像特征进行预后评估的库。

Moddicom: a complete and easily accessible library for prognostic evaluations relying on image features.

作者信息

Dinapoli Nicola, Alitto Anna Rita, Vallati Mauro, Gatta Roberto, Autorino Rosa, Boldrini Luca, Damiani Andrea, Valentini Vincenzo

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:771-4. doi: 10.1109/EMBC.2015.7318476.

Abstract

Decision Support Systems (DSSs) are increasingly exploited in the area of prognostic evaluations. For predicting the effect of therapies on patients, the trend is now to use image features, i.e. information that can be automatically computed by considering images resulting by analysis. The DSSs application as predictive tools is particularly suitable for cancer treatment, given the peculiarities of the disease -which is highly localised and lead to significant social costs- and the large number of images that are available for each patient. At the state of the art, there exists tools that allow to handle image features for prognostic evaluations, but they are not designed for medical experts. They require either a strong engineering or computer science background since they do not integrate all the required functions, such as image retrieval and storage. In this paper we fill this gap by proposing Moddicom, a user-friendly complete library specifically designed to be exploited by physicians. A preliminary experimental analysis, performed by a medical expert that used the tool, demonstrates the efficiency and the effectiveness of Moddicom.

摘要

决策支持系统(DSS)在预后评估领域的应用越来越广泛。为了预测治疗对患者的效果,目前的趋势是使用图像特征,即通过分析生成的图像自动计算得到的信息。鉴于癌症这种疾病具有高度局部化且会导致巨大社会成本的特点,以及每个患者都有大量可用图像,DSS作为预测工具的应用特别适用于癌症治疗。在当前技术水平下,存在一些用于处理图像特征以进行预后评估的工具,但它们并非为医学专家设计。由于这些工具没有集成所有所需功能,如图像检索和存储,因此需要很强的工程或计算机科学背景。在本文中,我们通过提出Moddicom来填补这一空白,Moddicom是一个专门为医生设计的用户友好型完整库。一位使用该工具的医学专家进行的初步实验分析证明了Moddicom的效率和有效性。

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