cat2tom / amd-das-brain-ct-segmentation

AMD-DAS-Brain-CT-Segmentation

This is the implementation of a paper titled: An Unsupervised Domain Adaptation Brain CT Segmentation Method Across Image Modalities and Diseases, currently under review by Journal Expert Systems with Applications. More details can be seen in our upcoming paper.

Built With

• PyTorch

Getting Started

Prerequisites

Python 3

CPU or NVIDIA GPU + CUDA CuDNN

Stage 1: Training of Image Synthesis Network

In the first stage, we train a pseudo-CT image synthesis network to minimize the difference between the two modalities.

Stage 2: Domain adaptation Segmentation

In the second stage, we use labelled pseudo-CT images (obtained from the first stage network) and unlabeled CT images to train domain adaptation segmentation network.

Matching Mechanism

In the training process of the image synthesis network, inputting the image pairs selected by this method can improve the performance of downstream tasks.

Contact

Daqiang Dong: [email protected]

Guanghui Fu: [email protected]; [email protected]