January 15, 2024Overview Built a deep learning-based medical imaging pipeline for detecting PUJ obstruction using ultrasound data. The project utilized transfer learning with state-of-the-art architectures and implemented advanced explainability tools. Key Features Deep learning-based detection Transfer learning implementation Model explainability Medical imaging processing Performance optimization Technical Implementation Model Architecture Implemented VGG16 Integrated InceptionV3 Utilized DenseNet121 Transfer learning optimization Explainability Tools t-SNE visualization Activation maps Model interpretation Performance analysis Data Processing Ultrasound data preprocessing Image augmentation Batch processing Validation pipeline Tech Stack Python TensorFlow Keras OpenCV VGG16 InceptionV3 DenseNet121 t-SNE Impact Enhanced detection accuracy Improved diagnosis support Model interpretability Efficient processing pipeline Project Gallery [Project screenshots to be added]
