HCC-TACE-Seg — Liver cancer multi-phase CT
QC-reimported HCC-TACE-Seg CT: TCIA DICOM series are split by within-series acquisition/stack metadata so multiphase scans do not concatenate into one volume.
No download, no account needed for the demo case — it opens read-only in the MedSeg editor. Sign up (free) to browse all 628 cases, run AI models, and segment.
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About this dataset
HCC-TACE-Seg captures the abdominal CT imaging of 105 patients with hepatocellular carcinoma (HCC) before and after trans-arterial chemoembolization (TACE) therapy. Multi-phase contrast-enhanced CT (arterial, portal-venous, delayed) — lets you see the same anatomy across enhancement phases.
Real clinical oncology data, multi-vendor, multi-phase. The original TCIA release includes DICOM-SEG segmentations for some cases, but those masks did not meet our quality standard for inclusion here, so this MedSeg dataset is provided as unlabeled image data.
This MedSeg import was rebuilt from the source TCIA DICOM series with explicit QC for HCC within-series stack concatenation. When a TCIA SeriesInstanceUID contains multiple CT acquisitions, those stacks are imported as separate MedSeg series. Non-image DICOM objects and any failed source series are recorded in the QC report directory.
| Fact | Value |
|---|---|
| Cases | 628 |
| Series | 628 |
| Size | 14.4 GB |
| Modality | CT |
| Reference masks | No |
| License | CC-BY-3.0 |
| Publisher | MD Anderson Cancer Center |
| Version | 2021-qc-split |
| DOI | 10.7937/TCIA.5FNA-0924 |
What you can do with it in MedSeg
Copied cases behave like normal project series — the public image bytes are linked, not duplicated, so copies are instant and take no extra storage.
- Copy cases into a project.
Filter, multi-select, copy. - Run AI segmentation.
TotalSegmentator, MRSegmentator, nnInteractive 3D clicks/scribbles, or text-prompted VoxTell. - Edit and measure.
Brush, lasso, fill, oblique planes, volumes in ml — in the browser. - Train your own nnU-Net.
Correct masks on a handful of cases and train a custom model on hosted GPUs.
Citation
If you use this dataset in your research, cite the source per its license terms.
Moawad, A. W., Fuentes, D., Khalaf, A., Blair, K., Szklaruk, J., Qayyum, A., et al. (2023). Multimodality annotated HCC cases with and without advanced imaging segmentation. Scientific Data, 10(1), 33.
License: CC-BY-3.0
Open data still carries obligations — attribution at minimum. Check the license terms and the source publication before publishing work built on this dataset. MedSeg is a research tool, not a medical device.
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