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December 30, 2024Journal of Information Systems Engineering & ManagementOpen Access

A Comparative Study of Deep Learning Techniques for Breast Cancer Detection Using Mammography, MRI, and Thermal Imaging

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Authors

CSC. J. Sandhya

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Overview

Comparative analysis demonstrates thermal imaging improves breast cancer detection over mammography and MRI, suggesting new pathways for diagnosis.

Key Points

  • Thermal imaging outperforms mammography and MRI for breast cancer detection, enhancing classification accuracy.
  • Dynamic thermal imaging achieved higher F1-score and AUC compared to mammography's CNN models and MRI's RCNN models.
  • Assessment across multiple modalities utilized accuracy, precision, recall, F1-score, and AUC for evaluation.
  • Results indicate potential for radiation-free imaging techniques in resource-limited healthcare settings.

Cite This Study

C. J. Sandhya (2024) studied this question.

synapsesocial.com/papers/68af658fad7bf08b1eae4db9https://doi.org/10.52783/jisem.v9i4s.12512
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Also Consider

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

  1. 1Advances in Thermal Imaging: A Convolutional Neural Network Approach for Improved Breast Cancer Diagnosis2024 · 3 citations
  2. 2Advancements in Breast Cancer Detection: A Holistic Evaluation of Deep Learning Models with Histology and Thermal Imaging Datasets2024
  3. 3Radiomics Meets Deep Learning: A Hybrid Approach for Breast Cancer Prediction from Mammographic Data2025
  4. 4Cross-Validation Deep Learning for Breast Cancer Detection Using DMR-IR Infrared Images2026
  5. 5An Automated Thermography-Based Breast Cancer Detection and Localization System2024 · 2 citations