PT Journal
AU AN Ruchai
   VI Kober
   KA Dorofeev
   VN Karnaukhov
   Mikhail Mozerov
TI Classification of breast abnormalities using a deep convolutional neural network and transfer learning
SO Journal of Communications Technology and Electronics
PY 2021
BP 778–783
VL 66
IS 6
DI 10.1134/S1064226921060206
AB A new algorithm for classification of breast pathologies in digital mammography using a convolutional neural network and transfer learning is proposed. The following pretrained neural networks were chosen: MobileNetV2, InceptionResNetV2, Xception, and ResNetV2. All mammographic images were pre-processed to improve classification reliability. Transfer training was carried out using additional data augmentation and fine-tuning. The performance of the proposed algorithm for classification of breast pathologies in terms of accuracy on real data is discussed and compared with that of state-of-the-art algorithms on the available MIAS database.
ER