Recent advances in deep learning are helping to identify, classify, and quantify patterns in medical images. Deep Learning helps to exploit hierarchical feature representations learned exclusively from data without proper domain-specific knowledge. Deep learning is rapidly becoming the state of the art in numerous medical applications.
Medical Image Analysis with Deep Learning training course will cover basic image processing techniques, different methods of features extractions, deep learning techniques (Autoencoders, CNN, RNN), and its application to Medical Image analysis (X-ray, OCT, Retinal Images, Brain Images, etc.). You can use these skills in order to develop newer technological innovations and regularize them for high-throughput clinical translation and usage.
By attending Medical Image Analysis with Deep Learning workshop, delegates will learn:
- Different Medical Image Modalities (X-rays, Magnetic Resonance, Ultrasonic, etc.).
- Basic Image operation with Python
- Texture in Medical Images and Classical Feature extraction.
- Neural Network, Autoencoder (Sparse and de-noising).
- Deep Learning with Convolutional Neural Network (CNN).
- Application of Deep Learning to Medical Image Analysis.
- Basic Python
- Data Scientists
- Data Analysts
- Machine Learning Engineers and Developers