BM_MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection

Installation

This code is based on Detectron.pytorch. Please see it for installation.

Environment

• Python (Tested on 3.6)
• PyTorch (Tested on 0.4.1.post2)

Data preparation

Download DeepLesion dataset here.

We provide coco-style json annotation files converted from DeepLesion. Unzip Images_png.zip and make sure to put files as following sturcture:

data
  ├──DeepLesion
        ├── annotations
        │   ├── deeplesion_train.json
        │   ├── deeplesion_test.json
        │   ├── deeplesion_val.json
        └── Images_png
              └── Images_png
               │    ├── 000001_01_01
               │    ├── 000001_03_01
               │    ├── ...

Training

To train MVP-Net with 9 slices model, run:

bash multi_windows_9_slices.sh train

We also provide our re-implementation of 3DCE, see 3DCE_*.sh for training and testing.

Testing

After training, put the model path into .sh file, after '--load_ckpt', and run:

bash multi_windows_9_slices.sh test