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 | Thoracic Malignancy Identification through Computed Tomography Scan Analysis |
|---|---|
| ABSTRACT | Lung cancer remains one of the leading causes of cancer-related mortality worldwide, primarily due to late-stage diagnosis and the inherent difficulty of manually interpreting complex CT scan images. This paper presents a machine learning-based approach for the automated detection of thoracic malignancies using computed tomography (CT) scan data. The proposed system integrates image preprocessing, deep feature extraction, and classification using the ResNet-18 convolutional neural network architecture to differentiate between cancerous and non-cancerous lung tissues. Preprocessing steps including noise reduction, histogram equalization, and image normalization standardize input data for optimal model performance. The model is trained and evaluated on a publicly available benchmark dataset and assessed using accuracy, precision, recall, F1-score, and confusion matrix analysis. Experimental results demonstrate that the system effectively identifies critical patterns associated with pulmonary malignancies, significantly reducing the probability of human error and providing a reliable decision-support tool for radiologists. A Streamlit-based web interface enables clinicians to upload CT images and receive automated predictions with confidence scores. This work underscores the transformative potential of deep learning in enhancing early detection and improving clinical outcomes in lung cancer diagnosis. |
| AUTHOR | PROF. MANJULA P, TANUSHREE B S, SNEHA U NARAGUND, YASHASWINI S, VIDYA T S Assistant Professor, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India UG Students, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404115 |
| pdf/115_Thoracic Malignancy Identification through Computed Tomography Scan Analysis.pdf | |
| KEYWORDS | |
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