FlexiCT

FlexiCT is a CT foundation model family trained through agglomerative continual pretraining from 2D slice-level anatomy to 3D volumetric reasoning and report-aligned vision-language understanding.

This family page links three child repos:

Repo	Input	Output	Recommended use
ricklisz/FlexiCT-2D	[B, 1, 512, 512] CT slices	CLS and patch tokens	Slice-level feature extraction, classification, visualization, registration features
ricklisz/FlexiCT-3D	[B, 1, 160, 160, 160] CT volumes	CLS and patch tokens	Whole-volume feature extraction and downstream 3D workflows
ricklisz/FlexiCT-3D-VLM	CT volumes plus text	Image/text embeddings and similarity scores	Report-aligned retrieval and zero-shot text-image scoring

Preprocessing presets

default is recommended for whole-volume 3D and 3D-VLM inference. It orients/resamples path inputs to LPS at 2 mm spacing when spacing is available, clips HU to [-1000, 1000], z-score normalizes, pads with the tensor minimum to at least 160^3, then center crops to 160^3. This best matches the released VLM evaluation path because it preserves physical scale better than globally resizing the anatomy.

local_path is a forgiving demo preset for arbitrary local CT files. It orients/resamples path inputs, clips, normalizes, pads to a cube, then trilinear-resizes to 160^3. It is robust to heterogeneous scans but less faithful to the VLM inference scripts because it globally rescales anatomy.

retrieval_roi is retrieval-specific. It orients/resamples, clips, normalizes, crops an ROI cube from coordinates, a mask, or a bounding box, pads if the crop hits an image boundary, then resizes to 160^3.

License

The released checkpoints are made available under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Code is MIT licensed in the source repository. Users must also comply with licenses and usage terms for the original datasets used to train the models.

Citation

@misc{li2026universalctrepresentations,
  title = {Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining},
  author = {Yuheng Li and Yuan Gao and Haoyu Dong and Yuxiang Lai and Shansong Wang and Mojtaba Safari and James E. Baciak and Xiaofeng Yang},
  year = {2026},
  eprint = {2605.21906},
  archivePrefix = {arXiv},
  primaryClass = {cs.CV},
  doi = {10.48550/arXiv.2605.21906},
  url = {https://arxiv.org/abs/2605.21906}
}

Medical disclaimer

FlexiCT is for research use only. It is not a medical device and is not a substitute for professional medical judgment.