Datasets
Models
Downloads: 1
Data:
Image
Tabular
Specialty:
Radiology
Medical Imaging Technique:
X-Ray
Medical Imaging Region:
Cervical Spine
Clinical Purpose:
Diagnosis
Task:
Classification
Detection
Segmentation
License:
Creative Commons Zero v1.0 Universal
Image
Tabular
Specialty:
Radiology
Medical Imaging Technique:
X-Ray
Medical Imaging Region:
Cervical Spine
Clinical Purpose:
Diagnosis
Task:
Classification
Detection
Segmentation
License:
Creative Commons Zero v1.0 Universal
[497519]:
/
README.md
25 lines (21 with data), 1.6 kB
RSNA 2022 Cervical Spine Fracture Detection
Clean metadata for train images
This dataset contains metadata extracted from training DICOM image files used in the RSNA 2022 Cervical Spine Fracture Detection competition.
Files Included
- meta-train: Original extracted metadata (use with caution)
- meta-train-clean: Cleaned version of
meta-train, easier to use - meta-segmentations: Metadata for images with segmentations, includes correct vertebra labels (C1–C7) extracted from segmentation masks
- meta-segmentation-clean: Cleaned version of
meta-segmentations - meta-train-with-vertebrae: Metadata for all training images, includes 88% accurate Random Forest predictions of the vertebra in each image
- train-segmented: Metadata for all train images with 95% accurate EffNetV2 vertebrae predictions (based on provided notebook)
- train-vert-fold4: Version of
train-segmentedcleaned and enriched via an image+tabular model; includes extra feature-engineered columns - train-vert: Final ensembled predictions from
train-segmentedandtrain-vert-fold4
Related Notebooks
- RSNA Fracture Detection – In-depth EDA
- Extracting Vertebrae C1, ..., C7