Mammography Classification Based on Convolutional Neural Network

DOI

10.2991/caai-18.2018.35How to use a DOI?

Keywords

mammography; classification; convolutional neural network; DDSM

Abstract

Limited by various conditions, the features of mammography images are difficult to extract, so it is hard to classify them. The paper proposed a method based on deep learning method to classify benign and malignant mammography images. The convolutional neural network concludes four convolution layers, four pool layers, and two full-connection layers, and a Softmax layer. The paper designed a new network architecture to improve the traditional one. As a result, we have done an experiment on the DDSM database. Compared with other classification methods, it shows that the method proposed in this paper is more effective than other methods.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Changjiang Zhang
AU  - Huanhuan Nie
PY  - 2018/08
DA  - 2018/08
TI  - Mammography Classification Based on Convolutional Neural Network
BT  - Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
PB  - Atlantis Press
SP  - 151
EP  - 154
SN  - 2589-4919
UR  - https://doi.org/10.2991/caai-18.2018.35
DO  - 10.2991/caai-18.2018.35
ID  - Zhang2018/08
ER  -