Abstract: This project proposes an Artificial Intelligence system for the early diagnosis and classification of bone cancer using deep learning methods, specifically Convolutional Neural Networks (CNN). The system processes medical imaging inputs like X-rays, MRIs, and CT scans. The methodology involves a pipeline of image preprocessing, tumor segmentation, feature extraction, and finally, benign or malignant classification. The solution achieves high performance, demonstrating its potential to assist radiologists and healthcare professionals by providing fast and reliable results. The system also incorporates cloud storage and a web-based interface, making it a scalable and efficient tool for telemedicine applications.
Keywords: Bone Cancer Detection, Convolutional Neural Network (CNN), Deep Learning, Medical Image Segmentation, Tumor Classification.
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DOI:
10.17148/IJARCCE.2025.141215
[1] Laxmi kantha K, SharanuBasava Aradhya, Shashank Gouda G Gali, Shreehari D R, Tarun Gowda D N, "AI-Driven Bone Cancer Detection using Segmentation and Classification with CNN," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.141215
