Liver Cancer Detection Using Ultrasound Images |Deep Learning IEEE Final Year Project with Full Code
🧫 Liver Cancer Detection on Ultrasound Images Using Deep Learning | IEEE-Based AI Project
This project presents an advanced deep learning solution for early liver cancer detection using ultrasound imaging. Our system automatically analyzes ultrasound images to classify whether a liver is cancerous or normal, providing a fast, reliable, and cost-effective diagnostic aid.
📚 Designed with reference to multiple IEEE research papers, this project involves:
Preprocessing of noisy ultrasound images (denoising, CLAHE, filtering)
Deep CNN architectures like ResNet50, EfficientNet, and hybrid models
Fully functional web application for real-time classification
Support for medical imaging standards and explainability techniques
🧠 Ideal For:
Final Year Engineering (CSE/IT/ECE), BSc/MSc/MCA students
AI in Healthcare research projects
Diagnostic AI startups and practitioners
Deep Learning learners focusing on medical datasets
💻 Technology Stack:
Python, TensorFlow/Keras
OpenCV for ultrasound image enhancement
CNN models: ResNet50, EfficientNet, VGG16/19
Web Deployment: Flask (Backend), HTML/CSS/JS (Frontend)
📦 What We Provide:
✅ Full source code + dataset
✅ IEEE format documentation (synopsis, report, PPT)
✅ Mentorship with detailed video explanation
✅ Customization & deployment assistance
📩 Contact for code, project support, and live mentorship:
📱 +91-8088605682
🌐 Website: smartaitechnologies.com
🏢 About Smart AI Technologies
We are experts in building IEEE Final Year Projects with complete support in:
✅ AI-based medical diagnostics
✅ Deep Learning, Computer Vision, IoT, and NLP
✅ Full-stack deployment with code, documentation & mentorship
🎓 Trusted by 8000+ students & researchers
🎥 Watch all demos on our YouTube: Smart AI Technologies
🔥 Hashtags:
#LiverCancerDetection #UltrasoundAI #DeepLearningProject #IEEEProject #MedicalAI #SmartAITechnologies #FinalYearProject #CancerDetectionAI #UltrasoundImageAI #CNNModel #AIinHealthcare