CS2

This is the official implementation of our proposed CS2 accepted by MICCAI 2022:

CS2: A Controllable and Simultaneous Synthesizer of Images and Annotations with Minimal Human Intervention

Highlight

The novelty of our work is three-fold:

• we develop a novel unsupervised mask-to-image synthesis pipeline that generates images controllably without human labeling;
• instead of directly using the numeric and disarranged unsupervised segmentation masks, which are cluttered with over-segmented super-pixels, we assign the mean Hounsfield unit(HU) value for each cluster in the unsupervised segmentation masks to obtain anordered and well-organized labeling;
• we propose a new synthesis network structure featured by multiple adaptive instance normalization (AdaIN) blocks that handles unaligned structural and tissue information.

Requirements

matplotlib==3.3.4

opencv-python==4.5.3.56

Pillow==8.3.2

pytorch-fid==0.2.0

scikit-image==0.17.2

scipy==1.5.4

torch==1.9.0

torchvision==0.10.0

Citation

This repository partially based on:

• pix2pixHD: High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs (code and paper);

• An implementation of Unsupervised Image Segmentation by Backpropagation: Faster and more elegant than origin version（code and paper)