IVPSQA

May 30, 2025 · View on GitHub

Invertible and Variable Augmented Network for Pretreatment Patient-Specific Quality Assurance Dose Prediction
Z. Zou, C. Gong, L. Zeng, Y. Guan, B. Huang, X. Yu, Q. Liu, M. Zhang
Journal of Imaging Informatics in Medicine, 1-12, 2024.
https://link.springer.com/article/10.1007/s10278-023-00930-w

#========================train========================= #DATA Prepare your own datasets for IVPSQA

You need to create at least two modality medical images from domain A /data/A and from domain B /data/B. Then you can train the model with the dataset flag --root1 './data/A' --root2 './data/B'. Optionally, you can create hold-out test datasets at ./data/A_test and ./data/B_test to test your model.

1to1---RTDose

python train.py --task=1to1 --out_path="./exps/"

2to1---RTDose+CT

python train.py --task=2to1 --out_path="./exps/"

resume training:

To fine-tune a pre-trained model, or resume the previous training, use the --resume flag

#========================test==========================

python test.py --task=2to1 --out_path="./exps/" --ckpt="./exps/2to1/checkpoint/latest.pth"

python test.py --task=1to1 --out_path="./exps/" --ckpt="./exps/1to1/checkpoint/latest.pth"

The training and testing pipeline of IVPSQA

A: Illustration of two different input modes of IVPSQA; B: The detailed architecture of IVPSQA

Visualization results of several comparison methods

  • Variable Augmented Network for Invertible Modality Synthesis and Fusion [Paper] [Code]

  • Variable augmentation network for invertible MR coil compression [Paper] [Code]

  • Virtual coil augmentation for MR coil extrapoltion via deep learning [Paper] [Code]

  • Variable Augmented Network for Invertible Decolorization (基于辅助变量增强的可逆彩色图像灰度化) [Paper] [Code]

  • Synthetic CT Generation via Invertible Network for All-digital Brain PET Attenuation Correction [Paper] [Code]

  • Variable augmented neural network for decolorization and multi-exposure fusion [Paper] [Code] [Slide]

  • Temporal Image Sequence Separation in Dual-tracer Dynamic PET with an Invertible Network [Code]

  • Spatial-Temporal Guided Diffusion Transformer Probabilistic Model for Delayed Scan PET Image Prediction [Paper] [Code]