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This repository contains a novel, multi-center colposcopy dataset created to address the limited representation of Bangladeshi patients in publicly available datasets.

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BUET Multi-Center Colposcopy Dataset

Overview

This repository contains a novel, multi-center colposcopy dataset created to address the limited representation of Bangladeshi patients in publicly available datasets. Curated in collaboration with multiple clinical sites in Dhaka, Bangladesh. This dataset provides a diverse and robust collection of clinical images and corresponding medical scores to aid in cervical cancer screening research.

Ethics & Data Privacy

Data collection and usage strictly adhered to ethical guidelines:

  • IRB Approval: Protocols were approved by BUET and the respective collaborating clinical hospitals.
  • Patient Privacy: A strict anonymization procedure was implemented to ensure no personally identifiable information (PII) was retained.
  • Informed Consent: Participants explicitly provided informed consent and maintained the right to withdraw throughout the process.

Dataset Structure

After filtering for cases with adequate documentation, the combined dataset comprises 768 patient cases, yielding 3,072 images in total.

For each patient, a four-image series was obtained, corresponding to the following applications:

  • Normal Saline
  • Acetic Acid
  • Green Filter
  • Lugol’s Iodine

Clinical Metadata Included:

  • Transformation zone type
  • Swede Score of five individual components (Aceto uptake,Margin, Vessel, Ledion Size, Iodine uptake)
  • Total Swede score (which can be mapped to a provisional diagnosis)
  • CIN Grading

Swede Score Distribution

The clinical reports document five distinct Swede Score characteristics. The score distributions across the dataset are summarized in the table below:

Characteristic Score 0 Score 1 Score 2
Aceto-White Uptake 293 409 66
Margin and Surface 441 312 15
Vessels 635 84 49
Lesion Size 336 357 75
Iodine Staining 207 439 122

Image Directory Structure

The images are organized into patient-specific folders. Each folder (e.g., 001) corresponds to a single patient case and contains a four-image series sequentially numbered based on the application type:

image_folder/
├── 001/                  # Patient/Case ID
│   ├── 001.jpg           # Normal Saline applied image
│   ├── 002.jpg           # Green Filtered image
│   ├── 003.jpg           # Acetic Acid (Aceto-white) uptake image
│   └── 004.jpg           # Lugol’s Iodine image
├── 002/ 
│   ├── ...

About

This repository contains a novel, multi-center colposcopy dataset created to address the limited representation of Bangladeshi patients in publicly available datasets.

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