Multimodal Ground Truth Datasets for Abdominal Medical Image Registration

Description

Resource Type: Data

This database includes registered multimodal image data. A CycleGAN network architecture was used to generate the synthetic data from the 4D extended cardiac–torso (XCAT) phantom and real patient data. Compared to real patient data, the synthetic data showed good agreement regarding the image voxel intensity distribution and the noise characteristics. The generated T1-weighted magnetic resonance imaging, computed tomography (CT), and cone beam CT images are inherently co-registered and can serve as ground truth for image segmentation and registration.