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October 11, 2025Edelweiss Applied Science and TechnologyOpen Access

Thermofusionnet for breast abnormality detection through visual and infrared thermal imaging using deep learning

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Authors

DGDipali GhatgeKRK. Rajeswari

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Overview

This model employs deep learning for accurate detection of breast cancer, suggesting new diagnostic methods.

Key Points

  • The ThermoFusionNet model improves breast cancer detection accuracy compared to traditional methods.
  • Experimental results indicate that malignant cases exhibit distinct thermal patterns, aiding reliable detection.
  • Integration of visual and infrared thermal imaging enhances the sensitivity and specificity of abnormality detection.
  • The study proposes adaptive filtering methods to reduce noise while preserving important image details.

Cite This Study

Ghatge et al. (2025) studied this question.

synapsesocial.com/papers/68e9b1c9ba7d64b6fc1327fahttps://doi.org/10.55214/2576-8484.v9i10.10383
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1An Automated Thermography-Based Breast Cancer Detection and Localization System2024 · 2 citations
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  3. 3Real-time thermography for breast cancer detection with deep learning2024 · 5 citations
  4. 4Advances in Thermal Imaging: A Convolutional Neural Network Approach for Improved Breast Cancer Diagnosis2024 · 3 citations
  5. 5AN EFFECTIVE VISION TRANSFORMER-AIDED INTELLIGENT EFFICIENTNET B7 WITH ADAPTIVE TUMOR SEGMENTATION FOR BREAST CANCER DIAGNOSIS USING THERMOGRAPHY IMAGES2025