International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Enhanced Mammographic Tumor Detection through AI Based Techniques |
|---|---|
| ABSTRACT | Breast cancer continues to be a main worldwide health issue, and identifying it at an initial stage greatly progresses the odds of actual treatment. Mammography is widely used for screening, yet reviewing these images can be slow and may differ from one radiologist to another.In this study, we introduce an AI-supported approach for analyzing mammogram images using CNNs, VGG16 transfer learning, and explainable AI methods. The proposed framework classifies the mammograms into Benign, Malignant, or Not Valid categories while embedding interpretability tools such as Grad-CAM and Integrated Gradients that highlight critical regions that influence the predictions. The system is deployed via a Flask-based web application and allows real-time inference, visualization of heatmaps, and user interaction. Experimental results prove that the model offers high classification accuracy, strong confidence scores, and effective visualization regarding tumor features. This work, focusing on transparency, reliability, and clinical applicability, presents another step forward in AI-aided diagnosis for breast cancer. |
| AUTHOR | NITHYA SHREE G M, POORVIKA C S, TRIVENI G, YASHASWINI, MARIA RUFINA P UG Student, Department of Computer Science & Engineering, GSSS Institute of Engineering & Technology for Women, Mysuru, Affiliated to VTU, Belagavi, Karnataka, India Assistant Professor, Department of Computer Science & Engineering, GSSS Institute of Engineering & Technology for Women, Mysuru, Affiliated to VTU, Belagavi, Karnataka, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312027 |
| pdf/27_Enhanced Mammographic Tumor Detection through AI Based Techniques.pdf | |
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