Tumor classification in automated breast ultrasound (ABUS) based on a modified extracting feature network

Author:

Zhuang Zhemin,Ding Wanli,Zhuang ShuxinORCID,Joseph Raj Alex NoelORCID,Wang JinhongORCID,Zhou WangORCID,Wei ChuliangORCID

Funder

Shantou University

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference37 articles.

1. Automated breast ultrasound system (ABUS): can it replace mammography as a screening tool? Egypt;Abd Elkhalek;J. Radiol. Nucl. Med,2019

2. Learning phrase representations using RNN encoder-decoder for statistical machine translation;Cho;EMNLP 2014 - 2014 Conf. Empir. Methods Nat. Lang. Process. Proc. Conf,2014

3. Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making;Ciritsis;Eur. Radiol.,2019

4. On denoising autoencoders trained to minimise binary cross-entropy;Creswell;arXiv e-prints arXiv:1708.08487,2017

5. Acute appendicitis: a meta-analysis of the diagnostic accuracy of US, CT, and MRI as second-line imaging tests after an initial US;Eng;Radiology,2018

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