Deep learning in mammography and breast histology, an overview and future trends

Author:

Hamidinekoo Azam,Denton Erika,Rampun Andrik,Honnor Kate,Zwiggelaar ReyerORCID

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

Reference143 articles.

1. Aggnet: Deep learning from crowds for mitosis detection in breast cancer histology images;Albarqouni;IEEE Trans. Med. Imaging,2016

2. American-Cancer-Society, 2016. What are the key statistics about breast cancer?. URL: http://www.cancer.org/cancer/breastcancer/detailedguide/breast-cancer-key-statistics.

3. Assessment of mitosis detection algorithms;AMIDA13,2017

4. Convolutional neural networks for mammography mass lesion classification;Arevalo,2015

5. Representation learning for mammography mass lesion classification with convolutional neural networks;Arevalo;Comput. Methods Programs Biomed.,2016

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