Automatic detection, segmentation and classification of abdominal aortic aneurysm using deep learning

H. Hong, U. U. Sheikh
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引用次数: 32

Abstract

In this paper, an automated method for the detection, segmentation and classification of Abdominal Aortic Aneurysm (AAA) region in computed tomography (CT) images is introduced. Deep Belief Network (DBN) is applied for the purpose of AAA detection and severity classification in this study. Optimum parameters for training the DBN are determined for the training data from the selected dataset. AAA region can be successfully segmented from the CT images and the result is comparable to the existing methods.
基于深度学习的腹主动脉瘤自动检测、分割和分类
本文介绍了一种腹主动脉瘤(AAA)区域的自动检测、分割和分类方法。本研究采用深度信念网络(Deep Belief Network, DBN)进行AAA检测和严重程度分类。从选定的数据集中确定训练DBN的最佳参数。该方法可以成功地从CT图像中分割出AAA区域,其结果与现有方法相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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