Work

Learning to Diagnose Cirrhosis with Liver Capsule Guided Ultrasound Image Classification

Year: 2017

Type: article

Abstract: 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.

Source: Sensors

DOI: 10.3390/s17010149

Authors: Xiang Liu, Jia Song, Shuo Wang, Jing Zhao, Yan Chen

Institutions: Shanghai University of Engineering Science, Fudan University, Second Military Medical University, Shanghai Changzheng Hospital

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,137