Call : (+91) 968636 4243
Mail :

Medical Image Analysis with Deep Learning

( Duration: 5 Days )

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



Introduction to Medical Images

  • X-ray and CT Imaging
  • Magnetic Resonance Imaging
  • Ultrasound Imaging
  • Optical Microscopy and Molecular Imaging

Basic Image operation with Python

  • Read and Display Image
  • Covert Colour Image to Grayscale Image
  • Cropping and Resizing an Image
  • Rotating Image
  • Histogram Equalization
  • Blurring an Image

Texture in Medical Images

  • Texture characterization – Statistical vs Structural
  • Co-occurrence Matrix
  • Orientation Histogram
  • Local Binary Pattern (LBP)
  • Texture from Fourier features
  • Wavelets
  • Feature extractions for Image (Medical/General)

Neural Network for Visual Computing

  • Simple Neuron
  • Neural Network formulation
  • Learning with Error Propagation
  • Gradient Checking and Optimization

Deep Learning

  • What is Deep Learning?
  • Families of Deep Learning
  • Multilayer Perceptron
  • Learning Rule
  • Autoencoders
  • Retinal Vessel Detection using Autoencoders

Stacked, Sparse, Denoising Autoencoders

  • Stacking Autoencoders
  • Ladder wise pre-training and End-to-End Pre-training
  • Denoising and Sparse Autoencoders
  • Ladder Training
  • End-to-End Training
  • Medical Image classification with Stacked Autoencoders

Convolutional Neural Network (ConvNet)

  • What is ConvNet?
  • Difference between Fully connected NN and ConvNet.
  • Stride, Padding, and Pooling
  • Deconvolution
  • ReLU Transfer Function

Image Classification with CNN

  • Convolutional Autoencoder
  • LeNet for Image Classification
  • AlexNet for Image Classification

Improving Deep Neural Network

  • Batch Normalization, Dropout
  • Tuning Hyper-parameters to improve performance of NN.
  • Learning Rate Annealing
  • Different Cost Functions

Deep CNN and its application to Medical Images

  • Vgg16, ResNet34, GooleNet, and DenseNet121
  • Transfer Learning
  • Pneumonia detection from Chest X-rays with Deep CNN.
  • White blood cell classification with CNN

Object Localization

  • Activation pooling for object localization
  • Region proposal Network
  • Sematic segmentation
  • UNet
  • Retinopathy Image segmentation with UNet

Spatio-Temporal Deep Learning

  • Understanding Video analysis
  • Recurrent Neural Network (RNN)
  • Long Short Term Memory (LSTM)
  • Activity recognition using 3D-CNN
  • Analysis of Brain Images

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 6,000 various courses on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.