AI-Driven Bone Cancer Detection using Segmentation and Classification with CNN

Abstract: This project suggests an early diagnosis and bone cancer classification AI system with the help of deep learning methods like Convolutional Neural Networks (CNN). The system takes medical image input like X-rays, MRIs, and CT scans. Image preprocessing, tumor segmentation, feature extraction, and benign/malignant classification are steps in the methodology. The solution has achieved 92.71% accuracy, 100% precision, and 93.95% recall, which is better than conventional machine learning algorithms like SVM. The system also incorporates cloud storage and remote diagnostic, making it scalable and efficient for telemedicine.

Keywords: Bone Cancer Detection, Convolutional Neural Network (CNN), Deep Learning, Medical Image Segmentation, Tumor Classification, Image Preprocessing, Python, TensorFlow, Keras, Flask, MongoDB, Cloud-Based Diagnosis, AI in Medical Imaging.