School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai 201203, China.
School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
Sensors (Basel). 2017 Jan 13;17(1):149. doi: 10.3390/s17010149.
This paper proposes a computer-aided cirrhosis diagnosis system to diagnose cirrhosis based on ultrasound images. We first propose a method to extract a liver capsule on an ultrasound image, then, based on the extracted liver capsule, we fine-tune a deep convolutional neural network (CNN) model to extract features from the image patches cropped around the liver capsules. Finally, a trained support vector machine (SVM) classifier is applied to classify the sample into normal or abnormal cases. Experimental results show that the proposed method can effectively extract the liver capsules and accurately classify the ultrasound images.
本文提出了一种基于超声图像的计算机辅助肝硬化诊断系统。我们首先提出了一种从超声图像中提取肝包膜的方法，然后，基于提取的肝包膜，我们微调了一个深度卷积神经网络（CNN）模型，从围绕肝包膜裁剪的图像块中提取特征。最后，应用训练好的支持向量机（SVM）分类器对样本进行正常或异常分类。实验结果表明，所提出的方法可以有效地提取肝包膜，并准确地对超声图像进行分类。
