metadata

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. With a comprehensive collection of real-world and simulated clinical data, this dataset supports tasks such as automated segmentation, disease detection, surgical planning, and outcome prediction.

📊 Dataset Summary

Feature	Details
🏥 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.
⚙️ Surgical Data	Surgical approach, implant type, disc herniation level, and follow-up notes.
📂 File Formats	Metadata in CSV and imaging data in simulated NIfTI paths.

💡 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.

🔍 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.

🛠️ 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`

📜 Citation

If you use this dataset, please cite it as follows:

💬 Contact

For inquiries, contact the dataset maintainer:
📧 A Taylor

🔒 Licensing

This dataset is licensed under Apache 2.0