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4DCT XCAT phantom dataset for "Resolving Variable Respiratory Motion From Unsorted 4D Computed Tomography", MICCAI2024

posted on 2024-07-01, 15:49 authored by Yuliang HuangYuliang Huang

The XCAT phantom dataset used in our paper "Resolving Variable Respiratory Motion From Unsorted 4D Computed Tomography", MICCAI 2024. For details on how to use the dataset, please visit If you find this dataset useful for your research, please cite our MICCAI paper.

Note: We thank Prof Paul Segars from Duke University for the permission of releasing this single simulation example. If you want to use the XCAT software, please contact him.

Introduction to the dataset:

A digital phantom of thoracic region with motion was generated by the 4DXCAT software [1] and post-processed by the cid-X software [2]. The simulation was controlled by two respiration traces, i.e. the motion of the chest and the diaphragm, which were measured from 2D Cine MRI from a real patient. The diaphragm trace was deliberately delayed by 1 second to add hysteresis, i.e. the breathing would follow different paths during inhalation and exhalation. The chest trace could simulate the skin marker or belt signals normally used to sort 4DCT data in clinical practice and was stored in the rpm_signal.txt file.

The phantom dataset consisted of images of thoracic regions at 182 timepoints in NIFTI format, each with size 355x280x115 voxels and resolution of 1x1x3 mm. Binary masks of the tumour were also provided for each timepoint. The dynamic volumes and tumor masks can be found in the compressed folder.

The ref_empty_image.nii.gz file is an image with zero voxel values that define the reference image space. The ref_tumor_mask.nii.gz is the ground-truth tumor mask at the time average position.


[1]Segars, W.P., Sturgeon, G., Mendonca, S., Grimes, J., Tsui, B.M.: 4d xcat phantom
for multimodality imaging research. Medical physics 37(9), 4902–4915 (2010)

[2]Eiben, B., Bertholet, J., Menten, M.J., Nill, S., Oelfke, U., McClelland, J.R.: Con-
sistent and invertible deformation vector fields for a breathing anthropomorphic
phantom: a post-processing framework for the xcat phantom. Physics in Medicine
& Biology 65(16), 165005 (2020)


EPSRC-funded UCL Center for Doctoral Training in Intelligent, Integrated Imaging in Healthcare (i4health) (EP/S021930/1)

Elekta Ltd., Crawley


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