Enhancing Breast Cancer Detection with AI: Ensuring Image Security and Diagnostic Precision Through Deep Learning Techniques

This study aims to explore and evaluate the effectiveness of Artificial Intelligence (AI), particularly Deep Learning (DL), as an innovative tool in the fight against breast cancer. As breast cancer remains one of the leading causes of mortality among women, numerous solutions have been proposed to address this pressing issue. AI, however, has emerged as a pivotal support system for radiologists, enhancing diagnostic accuracy and efficiency. Therefore, the study focuses on two key approaches i.e. image classification and pixel segmentation. While image classification provides valuable insights, it faces certain limitations, prompting the adoption of pixel segmentation as a more advanced method. Pixel segmentation offers detailed, essential information that, when combined with the expertise of medical professionals, has the potential to significantly enhance early detection and prevention strategies. By leveraging the synergy between AI and expert analysis, this approach represents a promising advancement in improving breast cancer diagnostics and patient outcomes.

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1109/isdfs65363.2025.11011981
Citations
1
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
2.48
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article

Enhancing Breast Cancer Detection with AI: Ensuring Image Security and Diagnostic Precision Through Deep Learning Techniques

Priyam Ganguly, Isha Mukherjee, Thrushna Matharasi, Sanjeev Lakkaraju
1 citations
AI in cancer detection
2.48
article

Enhancing Breast Cancer Detection with AI: Ensuring Image Security and Diagnostic Precision Through Deep Learning Techniques

Priyam Ganguly, Isha Mukherjee, Thrushna Matharasi, Sanjeev Lakkaraju
article en
1 citations

Abstract

This study aims to explore and evaluate the effectiveness of Artificial Intelligence (AI), particularly Deep Learning (DL), as an innovative tool in the fight against breast cancer. As breast cancer remains one of the leading causes of mortality among women, numerous solutions have been proposed to address this pressing issue. AI, however, has emerged as a pivotal support system for radiologists, enhancing diagnostic accuracy and efficiency. Therefore, the study focuses on two key approaches i.e. image classification and pixel segmentation. While image classification provides valuable insights, it faces certain limitations, prompting the adoption of pixel segmentation as a more advanced method. Pixel segmentation offers detailed, essential information that, when combined with the expertise of medical professionals, has the potential to significantly enhance early detection and prevention strategies. By leveraging the synergy between AI and expert analysis, this approach represents a promising advancement in improving breast cancer diagnostics and patient outcomes.

Cleveland State University (US), Pace University (US), Widener University (US), University of Bridgeport (US)
Good health and well-being
Openalex Percentile: Top 10%
AI in cancer detection
2.48
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Enhancing Breast Cancer Detection with AI: Ensuring Image Security and Diagnostic Precision Through Deep Learning Techniques — Priyam Ganguly, Isha Mukherjee, et al. · (2025) | TGRS Research Map | TGRS