提高超声造影光流对肝局灶性病变的诊断价值

2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI:10.1109/SYNASC57785.2022.00048

Cristina Laura Sîrbu, G. Simion, C. Căleanu

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引用次数: 0

摘要

我们提出了一种基于光流计算的自动获取感兴趣区域超声图像的方法。结合核相关滤波器跟踪算法和异常深度卷积神经网络架构，我们的解决方案在使用对比度增强超声自动诊断肝脏病变方面提供了最先进的结果(准确率超过90%)。

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Improving the Diagnostic of Contrast Enhanced Ultrasound Imaging using Optical Flow for Focal Liver Lesion Detection

Our proposal aims an automatic method used for obtaining the ultrasound image of a region of interest based on the optical flow computation. Combined with a kernel correlation filter tracking algorithm and a Xception deep convolutional neural network architecture, our solution provides state-of-the-art results (over 90% accuracy) in the automatic diagnosis of liver lesion using contrast enhanced ultrasound.

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2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

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