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Dataset

Tcia Cervicalcancer

by Angelou0516 hf-dataset--angelou0516--tcia_cervicalcancer
Free2AITools Nexus Index
58.9 Top 100%
S: Semantic 50
A: Authority 61
P: Popularity 50
R: Recency 90
Q: Quality 50
Tech Context
Vital Performance
0 DL / 30D
0.0%
Data Integrity 58.9 FNI Score
- Size
- Rows
Parquet Format
- Tokens
Dataset Information Summary
Entity Passport
Registry ID hf-dataset--angelou0516--tcia_cervicalcancer
License CC-BY-4.0
Provider huggingface
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Cite this dataset

Academic & Research Attribution

BibTeX
@misc{hf_dataset__angelou0516__tcia_cervicalcancer,
  author = {Angelou0516},
  title = {Tcia Cervicalcancer Dataset},
  year = {2026},
  howpublished = {\url{https://huggingface.co/datasets/Angelou0516/TCIA_CervicalCancer}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
Angelou0516. (2026). Tcia Cervicalcancer [Dataset]. Free2AITools. https://huggingface.co/datasets/Angelou0516/TCIA_CervicalCancer

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Full Specifications [+]

âš–ī¸ Free2AITools Nexus Index V2.0

Semantic (S) 50
Authority (A) 61
Popularity (P) 50
Recency (R) 90
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Tcia Cervicalcancer: Semantic (S:50), Authority (A:61), Popularity (P:50), Recency (R:90), Quality (Q:50).

Free2AITools Nexus Index

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Dataset Specification

TCIA_CervicalCancer (CC-Tumor-Heterogeneity)

Longitudinal multi-parametric MRI + 18F-FDG PET/CT collection of locally advanced cervical cancer patients undergoing chemoradiation, with radiation-oncologist tumor contours (RTSTRUCT) defined on T2-weighted MRI as the gold standard. Each patient was imaged at three time points spanning the chemoradiation course.

Dataset Details

Field Value
Modalities MR (T1W, T2W, DCE, DWI), 18F-FDG PET, CT
Body part Cervix / pelvis
Task 3D tumor segmentation on T2W MRI (longitudinal)
Patients 23 (CCTH-A01 â€Ļ CCTH-A12, CCTH-B01 â€Ļ CCTH-B11)
Time points 3 per patient — Baseline (0 Gy) / Early (20–25 Gy, 2–2.5 wk) / Mid-treatment (45–50 Gy, 4–5 wk)
Studies 171
Series 821
Images 131,556 DICOM slices
MR series 523 (15.91 GB)
CT series 65 (11.48 GB)
PET series 68 (0.99 GB)
RTSTRUCT files 68 (≈ 23 patients × 3 time points; CCTH-A06 has 2)
REG (registration) files 97
Format DICOM (images) + DICOM RTSTRUCT (contours) + DICOM REG (registrations)
License CC BY 4.0

Segmentation

Tumor contours are stored as DICOM RTSTRUCT files in segmentations/. Each RTSTRUCT references a single MR T2W sagittal series via ReferencedFrameOfReferenceSequence → RTReferencedStudySequence → RTReferencedSeriesSequence.SeriesInstanceUID — that referenced series is the image volume the contour is defined on. ROI names follow Ut-MRT2-Sag-{1|2|3} where the trailing index matches the time point (1 = Baseline, 2 = Early, 3 = Mid-treatment), and StructureSetName carries Timepoint{1|2|3}.

The collection paper describes contours as tumor volume only — no OARs and no lymph nodes, drawn by the study radiation oncologists with T2W MRI chosen for its highest soft-tissue contrast for cervical tumor delineation.

Structure

text
images_mr////*.dcm     # MR (T1W, T2W, DCE, DWI variants)
images_ct////*.dcm     # CT
images_pt////*.dcm     # PET
segmentations////*.dcm  # RTSTRUCT (one per time point)
registrations////*.dcm  # DICOM REG (PET/CT ↔ MR coregistration)
series_to_patient.json                                                  # series-level index

PatientID ranges over CCTH-A01..A12 and CCTH-B01..B11. StudyDescription in each RTSTRUCT carries MR1 / MR2 / MR3, identifying the time point. CCTH-B11 has no CT series; CCTH-A06 has 2 RTSTRUCTs (one time point missing).

Source

Citation

bibtex
@misc{mayr2023ccth,
  author    = {Mayr, N. and Yuh, W. T. C. and Bowen, S. and Harkenrider, M. and
               Knopp, M. V. and Lee, E. Y.-P. and Leung, E. and Lo, S. S. and
               Small Jr., W. and Wolfson, A. H.},
  title     = {Cervical Cancer -- Tumor Heterogeneity: Serial Functional and
               Molecular Imaging Across the Radiation Therapy Course in
               Advanced Cervical Cancer (Version 1) [Data set]},
  year      = {2023},
  publisher = {The Cancer Imaging Archive},
  doi       = {10.7937/ERZ5-QZ59}
}

@article{bowen2017radiomic,
  author  = {Bowen, S. R. and Yuh, W. T. C. and Hippe, D. S. and Wu, W. and
             Partridge, S. C. and Elias, S. and Jia, G. and Huang, Z. and
             Sandison, G. A. and Nelson, D. and Knopp, M. V. and Lo, S. S. and
             Kinahan, P. E. and Mayr, N. A.},
  title   = {Tumor radiomic heterogeneity: Multiparametric functional imaging
             to characterize variability and predict response following
             cervical cancer radiation therapy},
  journal = {Journal of Magnetic Resonance Imaging},
  volume  = {47},
  number  = {5},
  pages   = {1388--1396},
  year    = {2017},
  doi     = {10.1002/jmri.25874}
}

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Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-dataset--angelou0516--tcia_cervicalcancer
slug
angelou0516--tcia_cervicalcancer
source
huggingface
author
Angelou0516
license
CC-BY-4.0
tags
task_categories:image-segmentation, license:cc-by-4.0, size_categories:n<1k, region:us, medical, mri, ct, pet, cervix, cervical-cancer, tumor-segmentation, longitudinal, chemoradiation, rtstruct, dicom, tcia

âš™ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag

📊 Engagement & Metrics

downloads
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