An experimental study on breast lesion detection and classification from ultrasound images using deep learning architectures

Author:

Cao Zhantao,Duan LixinORCID,Yang Guowu,Yue Ting,Chen Qin

Funder

The Foundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Radiology Nuclear Medicine and imaging

Reference38 articles.

1. Cheng HD, Shan J, Ju W, Guo YH, Zhang L. Automated breast cancer detection and classification using ultrasound images: A survey. Pattern Recog. 2010; 43:299–317.

2. Zhang H, Wang KF, Wang FY. Advances and Perspectives on Applications of Deep Learning in Visual Object Detection. Acta Automatica Sinica. 2017; 43:1289–305.

3. Huang KQ, Ren WQ, Tan TN. A review on image object classification and detection. Chinese J Comput. 2014; 37:1225–40.

4. Dense features. Available from: https://en.wikipedia.org/wiki/Scale-invariant_feature_transform#Features . Accessed 5 Aug 2013.

5. Lowe DG. Distinctive image features from scale-invariant keypoints. Int J Comput Vision. 2004; 60:91–110.

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