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README.md

@@ -26,15 +26,15 @@ A multimodal dataset of **979 chest X-ray examinations**, each with:
 
 1. **Chest X-ray image** (full-resolution PNG, anonymised)
 2. **Consensus image-level labels** (37 radiological findings, agreed by two expert radiologists with adjudication)
-3. **Bounding box annotations** on the image (localising each finding)
+3. **Bounding box annotations** on the image from each annotator independently (localising each finding)
 4. **Original radiology report text**
 5. **Report span annotations** (token-level labels across 45 categories)
 
-This dataset combines resources from two annotation processes described in the papers below. The image-level labels and bounding boxes were produced through a consensus process involving two experienced radiologists with a third senior radiologist adjudicating disagreements. The report text annotations were produced independently by a separate team of radiologists.
+This dataset combines resources from two annotation processes described in the papers below. The image-level consensus labels were agreed by two experienced radiologists with a third senior radiologist adjudicating disagreements. Individual bounding boxes from each annotator are provided separately (identified by the `annotator` field), allowing researchers to study inter-annotator agreement or merge boxes as needed. The report text annotations were produced independently by a separate team of radiologists.
 
 **Website:** [x-raydar.info](https://x-raydar.info)
-**X-ray classifier:** [dnamodel/xraydar-cv](https://huggingface.co/dnamodel/xraydar-cv)
-**Report classifier:** [dnamodel/xraydar-nlp](https://huggingface.co/dnamodel/xraydar-nlp)
+**X-ray classifier:** [dnamodel/xraydar-cv](https://huggingface.co/dnamodel/xraydar-cv) · [Code](https://github.com/gmontana/xraydar-cv)
+**Report classifier:** [dnamodel/xraydar-nlp](https://huggingface.co/dnamodel/xraydar-nlp) · [Code](https://github.com/gmontana/xraydar-nlp)
 **Full annotated reports (29,756):** [dnamodel/xraydar-reports](https://huggingface.co/datasets/dnamodel/xraydar-reports)
 
 ## Dataset Structure
@@ -55,8 +55,8 @@ Each line in `annotations.jsonl` is a JSON object:
   "image_file": "images/1858.png",
   "consensus_labels": ["consolidation", "mediastinum_widened", "unfolded_aorta", "volume_loss"],
   "bounding_boxes": [
-    {"label": "consolidation", "x_min": 1200, "y_min": 800, "x_max": 1500, "y_max": 1100},
-    {"label": "mediastinum_widened", "x_min": 700, "y_min": 200, "x_max": 1000, "y_max": 600}
+    {"label": "consolidation", "annotator": "705", "x_min": 1200, "y_min": 800, "x_max": 1500, "y_max": 1100},
+    {"label": "mediastinum_widened", "annotator": "703", "x_min": 700, "y_min": 200, "x_max": 1000, "y_max": 600}
   ],
   "report_text": "There is consolidation in the left lower zone...",
   "report_tokens": ["There", "is", "consolidation", "in", "the", "..."],
@@ -73,7 +73,7 @@ Each line in `annotations.jsonl` is a JSON object:
 | Field | Source | Description |
 |-------|--------|-------------|
 | `consensus_labels` | Two radiologists + adjudication | Agreed image-level findings (37 classes) |
-| `bounding_boxes` | Same two radiologists | Spatial localisation of findings on the image |
+| `bounding_boxes` | Two radiologists independently | Spatial localisation of findings, with `annotator` ID per box |
 | `report_text` | Historical clinical report | Original free-text report written at time of exam |
 | `report_spans` | Separate annotation team | Token-level finding labels extracted from the report text (45 classes) |
 | `report_labels` | Derived from `report_spans` | Report-level labels (findings mentioned in text) |
@@ -134,7 +134,7 @@ print(f"Report: {exam['report_text'][:100]}...")
 ## Data Provenance
 
 - **Images**: Frontal chest X-rays from three UK NHS hospital networks (2006–2019), extracted from DICOM as anonymised PNGs at native resolution.
-- **Image annotations**: Produced using the AnnotateX platform. Two experienced radiologists independently annotated each image with finding labels and bounding boxes. Disagreements were reviewed and resolved with a third senior radiologist.
+- **Image annotations**: Produced using the AnnotateX platform. Two experienced radiologists independently annotated each image with finding labels and bounding boxes. Image-level consensus labels were agreed through adjudication with a third senior radiologist. Individual bounding boxes from each annotator are preserved with their annotator IDs.
 - **Report text**: Historical free-text radiology reports associated with each examination.
 - **Report annotations**: 29,756 reports were manually annotated by ten radiologists using the AnnotateX platform, with span-level labels across 45 categories.