| --- |
| license: cc-by-3.0 |
| task_categories: |
| - image-segmentation |
| tags: |
| - medical |
| - ct |
| - mediastinum |
| - abdomen |
| - lymph-node |
| - lymph-node-segmentation |
| - dicom |
| - dicom-seg |
| - nifti |
| - tcia |
| pretty_name: CT Lymph Nodes |
| size_categories: |
| - n<1K |
| --- |
| |
| # CT Lymph Nodes (Roth et al., NIH) |
|
|
| 176 chest + abdomen CT scans with manually-traced voxel-wise mediastinal and |
| abdominal lymph node segmentations. The collection underpins the Roth 2014 |
| detection benchmark and Seff 2015 segmentation benchmark, and remains a |
| widely-cited reference for thoracic-abdominal lymph node CADe work. |
|
|
| ## Dataset Details |
|
|
| | Field | Value | |
| |---|---| |
| | Modality | CT | |
| | Body part | Mediastinum + Abdomen | |
| | Task | 3D binary segmentation (foreground = lymph nodes) | |
| | Patients | 176 (90 mediastinal + 86 abdominal) | |
| | Studies | 176 | |
| | CT series | 176 | |
| | SEG series (V5 DICOM-SEG) | 176 (one per patient) | |
| | NIfTI masks (V4) | 176 (one per patient, in `supplementary/MED_ABD_LYMPH_MASKS.zip`) | |
| | Images (slices) | 110,179 CT DICOM slices | |
| | Annotated nodes | 983 (388 mediastinal + 595 abdominal) | |
| | Format | DICOM (CT, DICOM-SEG) + NIfTI (legacy masks) | |
| | License | CC BY 3.0 | |
|
|
| ## Anatomical Subsets |
|
|
| The collection is partitioned by **anatomical region** (no ML train/val/test |
| split is prescribed). Patient ID prefix encodes the subset: |
|
|
| | Subset | Patients | Annotated nodes | Measurement convention | |
| |---|---|---|---| |
| | **`MED_LYMPH_*`** | 90 | 388 | Shortest axis only (RECIST) | |
| | **`ABD_LYMPH_*`** | 86 | 595 | Longest + shortest axis (axial view) | |
|
|
| ## Mask Sources |
|
|
| The collection ships three companion annotation archives. **`MASKS`** is the |
| recommended ground truth; the other two are pre-existing detector inputs from |
| the original CADe pipeline and are retained here for reproducibility. |
|
|
| | Source | Role | Path on HF | |
| |---|---|---| |
| | **DICOM-SEG (V5, 2023-03-31)** ★ | Recommended GT — per-patient binary lymph-node masks, aligned to source CT via per-frame `DerivationImageSequence`. | `segmentations/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm` | |
| | **NIfTI masks (V4, 2015-12-14)** | Same voxel-wise GT as DICOM-SEG, expressed in NIfTI. | `supplementary/MED_ABD_LYMPH_MASKS.zip` | |
| | **Annotations (centroids)** | Lymph-node centroid points and RECIST size measurements (`.mps`, `.txt`). | `supplementary/MED_ABD_LYMPH_ANNOTATIONS.zip` | |
| | **Candidates (CADe detections)** | Computer-generated positive/negative candidate lists from Cherry/Liu SPIE 2014 — detector proposals, **not** ground truth. | `supplementary/MED_ABD_LYMPH_CANDIDATES.zip` | |
|
|
| **Recommended GT: DICOM-SEG masks (V5).** TCIA wiki explicitly directs citing |
| Seff 2015 (MICCAI 2015, DOI 10.1007/978-3-319-24571-3_7) when using these |
| masks. The DICOM-SEG representation was added in V5 (2023) and aligns to each |
| source CT slice via standard DICOM cross-references. The NIfTI masks (V4) |
| contain the same delineations and are also provided for legacy compatibility. |
| |
| The TCIA wiki notes the centroid annotations and the masks were produced |
| independently and their indexing is **not aligned** — a loader that needs both |
| must key on patient ID, not on node index within a patient. |
| |
| ## Structure |
| |
| ``` |
| images/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm # CT |
| segmentations/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm # DICOM-SEG |
| supplementary/MED_ABD_LYMPH_MASKS.zip # NIfTI masks |
| supplementary/MED_ABD_LYMPH_ANNOTATIONS.zip # centroid .mps files |
| supplementary/MED_ABD_LYMPH_CANDIDATES.zip # CADe proposals |
| series_to_patient.json # series-level metadata |
| ``` |
| |
| `PatientID` follows the pattern `MED_LYMPH_NNN` (90 cases) or |
| `ABD_LYMPH_NNN` (86 cases). The DICOM-SEG references its source CT via |
| `ReferencedSeriesSequence` (top-level CT SeriesInstanceUID) and |
| `PerFrameFunctionalGroupsSequence -> DerivationImageSequence -> |
| SourceImageSequence` (per-frame source CT SOPInstanceUID). |
| |
| `series_to_patient.json` lists every CT and SEG series with `PatientID`, |
| `StudyInstanceUID`, `SeriesInstanceUID`, `Modality`, `SeriesDescription`, |
| `ImageCount`, `FileSize`, and the on-disk relative path, so loaders can index |
| patients without crawling the DICOM headers. |
| |
| ## Notes for Loaders |
| |
| - **DICOM-SEG -> labelmap**: use `pydicom-seg` or `dcmqi`'s `segimage2itkimage` |
| for an aligned 3D label volume. Alternatively, load the NIfTI from |
| `supplementary/MED_ABD_LYMPH_MASKS.zip` and resample it to the CT grid. |
| - **No prescribed split**: a single train split covering all 176 patients. |
| Downstream tasks may carve out evaluation patients by patient ID; the |
| anatomical subset (MED vs ABD) is the natural stratification axis. |
| - **Subset detection**: the patient-ID prefix (`MED_` vs `ABD_`) is the |
| authoritative subset label. |
| |
| ## Source |
| |
| - TCIA collection: https://www.cancerimagingarchive.net/collection/ct-lymph-nodes/ |
| - DOI: `10.7937/K9/TCIA.2015.AQIIDCNM` |
| - Released: V5 on 2023-03-31 (DICOM-SEG version of masks added). Fully public, |
| no registration required since 2025-07-07. |
| |
| ## Citation |
| |
| ```bibtex |
| @misc{roth2015ctlymphnodes, |
| author = {Roth, Holger and Lu, Le and Seff, Ari and Cherry, Kevin M. and |
| Hoffman, Joanne and Wang, Shijun and Liu, Jiamin and |
| Turkbey, Evrim and Summers, Ronald M.}, |
| title = {A new 2.5D representation for lymph node detection in CT [Dataset]}, |
| year = {2015}, |
| publisher = {The Cancer Imaging Archive}, |
| doi = {10.7937/K9/TCIA.2015.AQIIDCNM} |
| } |
| |
| @inproceedings{roth2014lymphnode, |
| author = {Roth, Holger R. and Lu, Le and Seff, Ari and Cherry, Kevin M. and |
| Hoffman, Joanne and Wang, Shijun and Liu, Jiamin and |
| Turkbey, Evrim and Summers, Ronald M.}, |
| title = {A New {2.5D} Representation for Lymph Node Detection Using |
| Random Sets of Deep Convolutional Neural Network Observations}, |
| booktitle = {Medical Image Computing and Computer-Assisted Intervention -- |
| {MICCAI} 2014}, |
| pages = {520--527}, |
| year = {2014}, |
| doi = {10.1007/978-3-319-10404-1_65} |
| } |
| |
| @inproceedings{seff2015lymphnodemasks, |
| author = {Seff, Ari and Lu, Le and Barbu, Adrian and Roth, Holger and |
| Shin, Hoo-Chang and Summers, Ronald M.}, |
| title = {Leveraging Mid-Level Semantic Boundary Cues for Automated |
| Lymph Node Detection}, |
| booktitle = {Medical Image Computing and Computer-Assisted Intervention -- |
| {MICCAI} 2015}, |
| year = {2015}, |
| doi = {10.1007/978-3-319-24571-3_7} |
| } |
| ``` |
| |
