Hi, I’m fairly new to this field but I had some experiences with deep learning so I thought I’m going to give this a try.
When I see the data, my first thought was using 3D U-Net since the data we processing is in 3D matrix representation. My colab notebook is here. Using 3D U-Net without any significant modification and no pre-processing, I achieved 0.3 F1 score and 0.539 Accuracy.
My pipeline is:
- Zero padding the test set into divide-able cube
- Divide the data into cubes
- Train with 3D U-Net
- Validate each test cubes then stack them together into final prediction cube
Some thought and future improvement
- No data augmentation was used
- Pre processing method such as filtering, normalizing or thresholding was not used
- The training was quite time-consuming at approx 30min/epoch, Im running this on colab pro
I’ll try to improve this and I would be very happy to receive any suggestion, thank you.