STANDUP Database - Readme File

Welcome to the STANDUP Database! This repository contains a collection of thermal and RGB images used for research on Infrared Thermography for ulcers detection in diabetic foot condition. The database consists of two main groups: diabetic individuals and healthy subjects.

Dataset Structure :
The database is organized into the following folders:

Diabetic Group:
•	R0: Low-risk group, comprising non-neuropathic and non-ischemic individuals.
•	R1: Medium-risk group, consisting of neuropathic individuals without ischemia.
•	R2: High-risk group, including individuals with ischemia.
			
Each subgroup (R0, R1, and R2) contains thermal images of patients at two time points: T0 and T10, which correspond to the acquisition before and after the application of the cold stress test, respectively. For example, the image R0-0001 represents the acquisition at T0 for a patient, and R0-0002 represents the acquisition at T10 for the same patient.
			
Healthy Group:
•	Images H-0001 to H-0039: Participants who did not undergo the cold stress test. 
•	Images H-0040 to H-0125: Images of control subjects who underwent the cold stress test.

Data Usage:
Researchers and practitioners interested in utilizing this database for their studies are free to do so. However, please make sure to acknowledge the original creators of the STANDUP Database in any publications or research works.

Citation:
Please cite the following reference when using the STANDUP Database in your research:

Bouallal D, Bougrine A, Harba R et al. STANDUP database of plantar foot thermal and RGB images for early ulcer detection [version 1; peer review: 1 approved]. Open Res Europe 2022, 2:77 (https://doi.org/10.12688/openreseurope.14706.1)

Contact Information:
For any inquiries or questions related to the database, please contact:
rachid.harba@univ-orleans.fr
doha.bouallal@uiz.ac.ma
Thank you for your interest in the STANDUP Database. We hope it proves to be a valuable resource for your research on Infrared Thermography for diabetic foot ulcers detection.