Radiology Dataset Guide Skill

Triggers

• "radiology dataset"
• "medical imaging data"
• "RSNA challenge"
• "MIMIC data access"
• "CheXpert download"
• "dataset comparison"
• "training data preparation"
• "public dataset"

Parameters

• task_type (required): ML/AI task being solved
  • detection - Abnormality/nodule/cancer detection
  • segmentation - Organ or lesion segmentation
  • classification - Disease or finding classification
  • reconstruction - Image reconstruction/enhancement
  • quantification - Measurement and feature extraction
• anatomy (optional): Body region or organ system
• modality (optional): Imaging modality preference
• access_requirements (optional): Data use restrictions
• commercial_use (optional): Boolean for commercial application intent

Dataset Inventory

Dataset	Modality	Primary Task	Access	Annotations
RSNA Bone Age	X-ray	Regression	Public	Age, quality
RSNA Pneumonia	Chest X-ray	Detection	Public	Bounding boxes
RSNA Brain Hemorrhage	CT	Detection	Public	Bounding boxes, type
NIH ChestX-ray14	Chest X-ray	Classification	Public	Labels
CheXpert	Chest X-ray	Classification	Institutional	Labels
MIMIC-CXR	Chest X-ray	Multi	PhysioNet	Labels, reports
CheXphoto	Chest X-ray	Classification	Public	Synth/real pairs
LUNA16	CT	Detection	Public	Nodule centers
KiTS	CT	Segmentation	Public	Kidney/tumor
BraTS	MRI	Segmentation	Research	Multi-modal seg
PANDA	Histology	Classification	Public	Biopsy grades
OBJ-CXR	Chest X-ray	Detection	Public	Bounding boxes

Output Format

Returns structured JSON with:

• Relevant datasets ranked by suitability
• Annotation quality and completeness
• Access procedure and requirements
• Key publications and benchmarks
• Preprocessing recommendations
• Compliance and ethics considerations

Usage Examples

task_type: detection
anatomy: lung
modality: CT

task_type: classification
anatomy: chest
commercial_use: true