A novel convolutional neural network model through histopathological images for the diagnosis of breast cancer
using BreakHis data
- Benign/Malignant Classification with
98.8%accuracy. - Sub-Benign Disease Classification with
95.5%accuracy. - Sub-Malignant Disease Classification with
92.8%accuracy.
# Typical tf.keras API usage
from breastnet import BreastNet
model = BreastNet(input_shape=..., n_classes=...)
model.compile(...)
history = model.fit(...)All training codes and historyEvaluation Results in Accuracy, F1-Macro, ROC-AUC.. metrics-
- see research folder for details.
M. Togaçar, K.B. Özkurt, B. Ergen et al., BreastNet: A novel ˘
convolutional neural network model through histopathological images for the diagnosis of breast
cancer, Physica A (2019), doi: https://doi.org/10.1016/j.physa.2019.123592 .
If you have any questions about the research, feel free to ask!
E-mail: kutsal_baran@hotmail.com
This project is licensed under the MIT LICENSE - see the LICENSE file for details.