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Helicobacter pylori infection detection from gastric X-ray images using KLFDA-based decision fusion

机译:使用基于KLFDA的决策融合技术从胃部X射线图像检测幽门螺杆菌感染

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This paper presents the performance improvement of Helicobacter pylori (H. pylori) infection detection using Kernel Local Fisher Discriminant Analysis (KLFDA)-based decision fusion. As the biggest contribution of this paper, the proposed method extracts more discriminative features based on KLFDA for the decision fusion. Since the decision fusion employed in this paper can consider not only the detection results but also the visual features, by calculating more discriminative features via KLFDA, more accurate decision fusion becomes feasible. Furthermore, experimental results show the effectiveness of the proposed method.
机译:本文介绍了基于内核局部Fisher判别分析(KLFDA)的决策融合技术对幽门螺杆菌(H. pylori)感染检测的性能改进。作为本文的最大贡献,该方法基于KLFDA提取了更多的判别特征用于决策融合。由于本文采用的决策融合不仅可以考虑检测结果,还可以考虑视觉特征,因此通过KLFDA计算更多的判别特征,可以实现更准确的决策融合。此外,实验结果表明了该方法的有效性。

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