Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks
Mihail Burduja, Radu Tudor Ionescu, Nicolae Verga, Sensors 2020, 20(19), 5611
Official URL: https://www.mdpi.com/1424-8220/20/19/5611/pdf
ArXiv URL: https://arxiv.org/abs/2008.00302
This is the official repository of "Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks".
RSNA Intracranial Hemorrhage Detection (https://www.kaggle.com/c/rsna-intracranial-hemorrhage-detection) model
ResNeXt + PCA + BiLSTM for 0.04989 on Private Test Dataset
Sequence Metadata Required: https://www.kaggle.com/mihailburduja/rsna-intracranial-sequence-metadata
Slices are resized to 256x256, embedding vector is resized to 120.
models.py contains the CNN and LSTM model
datasets.py contains the torch Datasets for CNN and for LSTM model
train_cnn.py trains the CNN and outputs PCA embeddings and predictions
train_lstm.py train the LSTM and outputs the submission file
License: CC BY-NC-ND
This software is released un the CC BY-NC-ND license agreement. The software can be used for non-commercial purposes only.