Dataset Card for Breast Thermography

This dataset contains calibrated breast thermography images, transformed from lossless radiometric JPEG images using the thermal parser tool. The calibration process leverages exiftool to generate a temperature text file from each image, with the final images stored in TIFF format for improved reproducibility and usability.

Dataset Details

Dataset Description

The original dataset was published on 5 February 2024 (Version 3) and is documented at Mendeley Data. It contains thermographic images of the female thorax area captured in a medical setting with a FLIR A300 camera. The dataset comprises three positions per patient (anterior, left oblique, and right oblique) and includes a variety of pathology results related to breast cancer research. Our contribution transforms the original JPEG images using the thermal parser repository to produce calibrated TIFF images along with a temperature calibration text file. This new format is intended to facilitate further analysis and experimentation. Additionally, clinical metadata has been used to generate descriptive text prompts via a custom Python function, using age, weight, heightand protocol information to facilitate multimodal research.

Curated by: Brayan Quintero, Miguel Pimiento, Guillermo Pinto, Julian León, Dana Villamizar.
Funded by [optional]: Universidad Nacional Abierta y a Distancia (UNAD) – additional details not provided.
License: CC BY NC 3.0 (as per the original dataset).

Dataset Sources [optional]

Repository: Mendeley Data Original Repository
Paper [optional]: DOI: 10.1016/j.dib.2024.110503

Uses

Direct Use

This dataset is suitable for research in breast imaging and thermography, including but not limited to:

Developing and testing image processing algorithms.
Analyzing temperature distributions for clinical decision support.
Conducting experiments in passive thermography in medical research.

Out-of-Scope Use

The dataset is not recommended for applications outside medical imaging and research.
Misuse in any diagnostic context without proper clinical validation is strongly discouraged.
Not intended for commercial use due to the CC BY NC 3.0 license.

Dataset Structure

The dataset is structured into training and testing splits. Each split contains calibrated TIFF images. The images follow the original capture protocol and include metadata about the capture settings and patient position (anterior, left oblique, right oblique). Alongside descriptive sentences generated from the clinical metadata using a custom Python function (see code snippet here).

Dataset Creation

Curation Rationale

The dataset was curated to enhance the usability of the original thermographic images by converting them from JPEG to a calibrated TIFF format. This transformation facilitates reproducible research and enables easier integration with modern image processing workflows. In addition, the integration of descriptive clinical metadata allows the clinical context to be incorporated into image analysis workflows.

Source Data

The source data comes from a dataset originally published on Mendeley Data. It includes thermographic images of the female thorax collected during the period from 2021 to 2022 in a hospital setting in Cali, Colombia.

Data Collection and Processing

Original Collection: Images were captured using a FLIR A300 camera in a medical office following the American Academy of Thermology (AAT) protocol.
Processing: The original lossless radiometric JPEG images were transformed using the thermal parser tool. This tool employs exiftool to extract temperature calibration data and generate a corresponding text file. The calibrated images are then saved in TIFF format for improved data fidelity.

Who are the source data producers?

The original dataset was produced by a group of contributors including:

Steve Rodriguez-Guerrero
Humberto Loaiza Correa
Andrés-David Restrepo-Girón
Luis Alberto Reyes
Luis Alberto Olave
Saul Diaz
Robinson Pacheco

Personal and Sensitive Information

The dataset contains medical images and related metadata. While no explicit personal identifiers are provided, users should be aware that the images originate from a clinical setting and caution should be exercised regarding patient privacy and data sensitivity.

Bias, Risks, and Limitations

The dataset reflects the clinical and demographic conditions of the patient cohort in Cali, Colombia, which may not generalize to other populations.
The calibration process depends on the accuracy of the thermal parser and exiftool, and potential errors in these tools might affect the temperature readings.

Recommendations

Users should be aware of the inherent biases in the clinical setting of data collection and the technical limitations of the calibration process. Further validation is recommended when applying these images in clinical or diagnostic research contexts.