This is the official code of our MICCAI 2025 paper Nora 🥳
conda create -n Nora python=3.7.16
conda activate Nora
pip install -r requirements.txt
Process MYO data with:
dataset/MYO/CAMUS_process.py,dataset/MYO/HMC_QU_process.py
├── BUS
│ ├── BUSI
│ │ ├── images
│ │ └── masks
│ ├── DatasetB
│ │ ├── BUS
│ │ │ ├── image
│ │ │ └── label
│ └── STU
│ └── BUSI
│ ├── img
│ └── label
│
├── Thyroid
│ ├── DDTI dataset
│ │ └── DDTI
│ │ └── 2_preprocessed_data
│ │ └── stage2
│ │ ├── p_image
│ │ └── p_mask
│ ├── tn3k
│ │ ├── trainval-image
│ │ └── trainval-mask
│
├── MYO
│ ├── CAMUS3K
│ │ ├── images
│ │ └── labels
│ └── HMC-QU
│ ├── images
│ └── labels
Please download the pretrained SAM model (provided by the original repository of SAM) and put it in the ./pretrained folder. What's more, we also provide well-trained models at Release. Please put it in the ./snapshot folder for evaluation.
BUS (BUSI → DatasetB, STU)
CUDA_VISIBLE_DEVICES=0 python train.py --source_root_path busi_dataset_path --target_root_path1 datasetb_dataset_path --target_root_path2 stu_dataset_path
Thyroid (TN3K->DDTI)
CUDA_VISIBLE_DEVICES=0 python train_thyroid.py --source_root_path tn3k_dataset_path --target_root_path ddti_dataset_path
MYO (CAMUS->HMC-QU)
CUDA_VISIBLE_DEVICES=0 python train_myo.py --source_root_path camus3k_dataset_path --target_root_path hmcqu_dataset_path