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+# ROI Classification Model
+
+[![TensorFlow 1.15](https://img.shields.io/badge/TensorFlow-1.15-FF6F00?logo=tensorflow)](https://github.com/tensorflow/tensorflow/releases/tag/v1.15.0)
+[![Python 3.6](https://img.shields.io/badge/Python-3.6-3776AB)](https://www.python.org/downloads/release/python-360/)
+
+![train-classifier](../imgs/Rad_Fig_v4_Classifier.png)
+
+## Training Setup
+
+Models are implemented with Tensorflow 1.15 and trained on NVIDIA GeForce RTX/GTX GPU devices with CUDA version 9 or 10.
+
+Classification model is developed with Keras sequential class, consisting of a stack of six convolution layers and two fully-connected layers that end with softmax activation for multi-class classification.
+
+## Weighted Categorical Cross-entropy Loss
+
+We use a cost-sensitive loss for training due to the highly imbalanced data distirbution.
+
+See Keras Github for more detailed discussion on the implementation:
+https://github.com/keras-team/keras/issues/2115
+
+
+## References
+- Keras official tutorial on image classification models: https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html
+