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---
datasets:
  - name: Anterior Cervical Discectomy Dataset (ACD)
  - description: "A high-quality dataset for AI model development in Anterior Cervical Discectomy (ACD), featuring clinical, imaging, and surgical data to advance research in automated image analysis, surgical planning, and outcome prediction."
  - license: "Apache 2.0"
  - tags:
    - medical-imaging
    - spine-surgery
    - segmentation
    - surgical-planning
    - AI-healthcare
  - languages:
    - en
---

## 🎯 **Anterior Cervical Discectomy Dataset (ACD)**

## 🎯 **Overview**
The **Anterior Cervical Discectomy (ACD) Dataset** is designed for research in AI applications for spine surgery. 

---

## πŸ“Š **Dataset Summary**
| **Feature**               | **Details**                                   |
|---------------------------|-----------------------------------------------|
| πŸ₯ **Clinical Data**       | 1200 patient records with demographic, medical, and surgical history. |
| 🧠 **Imaging Data**        | High-resolution CT and MRI scans across pre-operative, intra-operative, and post-operative stages. |
| 🎯 **Annotations**          | Paths to synthetic segmentations for spinal structures and annotations by expert spine surgeons. |
| βš™οΈ **Surgical Data**        | Surgical approach, implant type, disc herniation level, and follow-up notes. |
| πŸ“‚ **File Formats**        | Metadata in CSV and imaging data in simulated NIfTI paths. |

---

## πŸ’‘ **Features**
### **1. Clinical Data**
- Patient demographics: Age, sex, weight, height.
- Medical history: Comorbidities, previous surgeries.
- Surgical details: Approach, level of disc herniation, implant type.

### **2. Imaging Data**
- Modalities: CT and MRI.
- Imaging protocols: T1-weighted, T2-weighted, and T2-FLAIR.
- Scan stages: Pre-operative, intra-operative, post-operative.
- Scanner metadata: Manufacturer and model.

### **3. Surgical and Post-Operative Data**
- Disc degeneration grade, spinal stenosis, and herniation presence.
- Surgical outcome classification: Successful or with complications.
- Follow-up notes summarizing patient recovery or issues.

---

## πŸ” **Usage**
This dataset is suitable for:
- **Automated Segmentation:** Efficient segmentation of vertebrae, discs, and spinal structures.
- **Disease Classification:** Detection of disc herniation, spinal stenosis, and degeneration.
- **Outcome Prediction:** Prediction of post-operative success and complications.

---

## πŸ› οΈ **File Organization**
- **Main CSV:** Contains metadata for all patient cases.
- **Synthetic Images:** Simulated paths for pre-operative, intra-operative, and post-operative scans.
- **Annotations:** Placeholder paths for potential spinal structure segmentations.

---

## 🎨 **Visual Example**
Below is an example row from the dataset:

| **Feature**              | **Example Value**                            |
|--------------------------|----------------------------------------------|
| Patient_ID               | `P0001`                                     |
| Age                      | `45`                                        |
| Imaging Modality         | `MRI`                                       |
| Disc Degeneration Grade  | `Moderate`                                  |
| Spinal Stenosis          | `Yes`                                       |
| Surgical Outcome         | `Successful`                                |
| Pre_Op_Image_Path        | `/simulated/path/P0001_pre_op_image.nii`    |

---

## πŸ“œ **Citation**
If you use this dataset, please cite it as follows:

---

## πŸ’¬ **Contact**
For inquiries, contact the dataset maintainer:  
πŸ“§ **A Taylor**  

---

## πŸ”’ **Licensing**
This dataset is licensed under **Apache 2.0**