# Comparing Results of Thermographic Images Based Diagnosis for Breast Diseases

arXiv: https://arxiv.org/abs/2208.14410 · HTML: https://mlsanity.com/paper/2208.14410/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 19 references that are in the map.
- First posted on arXiv 30 Aug 2022.

## Built on by (most cited first, 3 of 3)

- [Towards the automated segmentation of epicardial and mediastinal fats: A multi-manufacturer approach using intersubject registration and random forest](https://mlsanity.com/paper/2605.29217/) (2026)
- [Proposal and study of statistical features for string similarity computation and classification](https://mlsanity.com/paper/2605.15110/) (2026)
- [A Context-Aware Middleware for Medical Image Based Reports: An approach based on image feature extraction and association rules](https://mlsanity.com/paper/2605.30699/) (2026)

## Abstract (arXiv)

This paper examines the potential contribution of infrared (IR) imaging in breast diseases detection. It compares obtained results using some algorithms for detection of malignant breast conditions such as Support Vector Machine (SVM) regarding the consistency of different approaches when applied to public data. Moreover, in order to avail the actual IR imaging's capability as a complement on clinical trials and to promote researches using high-resolution IR imaging we deemed the use of a public database revised by confidently trained breast physicians as essential. Only the static acquisition protocol is regarded in our work. We used lO2 IR single breast images from the Pro Engenharia (PROENG) public database (54 normal and 48 with some finding). These images were collected from Universidade Federal de Pernambuco (UFPE) University's Hospital. We employed the same features proposed by the authors of the work that presented the best results and achieved an accuracy of 61.7 % and Youden index of 0.24 using the Sequential Minimal Optimization (SMO) classifier.