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+# Brain Hemorrhage Extended (BHX): Bounding Box Extrapolation from Thick to Thin Slice CT Images
+
+**Creators**:  
+Eduardo Pontes Reis, Felipe Nascimento, Mateus Aranha, Fernando Mainetti Secol, Birajara Machado, Marcelo Felix, Anouk Stein, Edson Amaro
+
+**Published**: July 29, 2020  
+**Version**: 1.1
+
+---
+
+## 📄 Citation
+
+Reis, E. P., Nascimento, F., Aranha, M., Mainetti Secol, F., Machado, B., Felix, M., Stein, A., & Amaro, E. (2020). *Brain Hemorrhage Extended (BHX): Bounding box extrapolation from thick to thin slice CT images* (version 1.1). PhysioNet. https://doi.org/10.13026/9cft-hg92
+
+### PhysioNet Standard Citation:
+
+Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). *PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals*. Circulation [Online]. 101 (23), pp. e215–e220.
+
+---
+
+## 🧠 Abstract
+
+BHX is a publicly available dataset with bounding box annotations for five types of acute hemorrhage as an extension of the [qure.ai CQ500 dataset](http://headctstudy.qure.ai/dataset). The dataset is intended to aid in developing machine learning solutions for hemorrhage detection and localization.
+
+---
+
+## 📌 Key Points
+
+- **39,668** bounding boxes in **23,409** images annotated for hemorrhage.
+- Built from the ~170k image **CQ500 dataset**.
+- Bounding boxes extrapolated from sparse thick-slice labeling to thin-slice images.
+- Supports machine learning applications for hemorrhage localization and diagnosis.
+
+---
+
+## 🧬 Background
+
+- Intracranial hemorrhage is a serious condition with a **40% one-month mortality rate**.
+- Head CT is the primary imaging modality.
+- Manual bounding box annotation is time-consuming; hence, extrapolation methods are used.
+- No existing public dataset includes **localization data** with bounding boxes until BHX.
+
+---
+
+## 🧪 Methods
+
+- Based on the **CQ500 dataset** (491 scans, 205 hemorrhage-positive).
+- Labeled by 3 neuroradiologists with varying experience.
+- Matching between thick and thin series was done via DICOM tag: `Image Position (patient)`.
+- Six types of hemorrhage labeled:  
+  - **Intraparenchymal**  
+  - **Subarachnoid**  
+  - **Intraventricular**  
+  - **Epidural**  
+  - **Acute Subdural**  
+  - **Chronic Subdural**
+
+---
+
+## 🗃️ Data Description
+
+### Annotation Stats:
+
+- **6,283** manually labeled bounding boxes in **3,558** images.
+- **39,668** extrapolated bounding boxes in **23,409** images.
+
+### Dataset Versions:
+
+1. `1_Initial_Manual_Labeling.csv`: Hand-drawn annotations on thick slices.
+2. `2_Extrapolation_to_All_Series.csv`: Extrapolated to all corresponding series.
+3. `3_Extrapolation_to_Selected_Series.csv`: Extrapolated only for selected soft-tissue thin-slice series.
+
+### Columns:
+
+- `SOPInstanceUID`: Unique DICOM image ID
+- `SeriesInstanceUID`: DICOM series ID
+- `StudyInstanceUID`: DICOM study ID
+- `data`: Bounding box coordinates (X, Y, width, height)
+- `labelName`: Hemorrhage type
+- `labelType`: Source of image (thick-slices, thin-slices, or other)
+
+---
+
+## 🔗 DICOM UID Mapping
+
+- Annotations are linked via DICOM tag: `0008,0018 – SOP Instance UID`.
+
+---
+
+## 📂 Original Images
+
+- Hosted at: [http://headctstudy.qure.ai/dataset](http://headctstudy.qure.ai/dataset)
+
+---
+
+## 🔍 Usage Notes
+
+- Unique resource for **bounding-box annotated hemorrhage images**.
+- Enables **benchmarking** and **development** of deep learning algorithms.
+- Includes extrapolated labels, some of which may have minor inaccuracies.
+- Future work should consider **interpolating bounding boxes** between slices for smoother transitions.
+
+---
+
+## 🖼️ Visual Inspection
+
+- Explore annotated images at:  
+  [https://public.md.ai/annotator/project/Y2qr6vqv/workspace](https://public.md.ai/annotator/project/Y2qr6vqv/workspace)
+
+---
+
+## 🙏 Acknowledgements
+
+- **qure.ai** – for publishing the CQ500 dataset.  
+- **MD.ai** – for providing the annotation platform.
+
+---
+
+## ⚠️ Conflicts of Interest
+
+- A.S. is employed by MD.ai, which provided the annotation platform.
+
+---
+
+## 📚 References
+
+1. van Asch C, et al. *The Lancet Neurology*, 2010.
+2. Heit J, et al. *Journal of Stroke*, 2017.
+3. Chang P, et al. *American Journal of Neuroradiology*, 2018.
+4. Goldstein J, Gilson A. *Current Treatment Options in Neurology*, 2011.
+5. Prevedello L, et al. *Radiology*, 2017.
+6. Chilamkurthy S, et al. *The Lancet*, 2018.
+7. Kuo W, et al. *PNAS*, 2019.
+8. RSNA ICH Detection. [Kaggle](https://www.kaggle.com/c/rsna-intracranial-hemorrhage-detection)
+9. Mirza S, Gokhale S. *IntechOpen*, 2017.
+10. Osborn A, et al. *Osborn’s Brain*, Elsevier, 2018.
+11. Weiss K, et al. *AJR*, 2011.
+12. DICOM Standard. [dicomstandard.org](https://www.dicomstandard.org)
+
+---