Full Scale Medical Image Analysis
This project involves applying image registration, segmentation and classification to retinal images.
Biomedical · Course
Advanced Medical Image Processing
An advanced course on Medical Image Processing.
- Duration
- 6 weeks
- Content
- 9 hours
- Projects
- 1
- Mode
- Online
OverviewWhat you'll
What you'll
be able to do.
- This course focuses on applying deep learning methods to various problems in the domain of medical image analysis.
- This course will cover classical approaches to medical image analysis such as registration and segmentation, basics of convolutional neural networks (CNNs), and strategies to perform efficient training of neural networks.
- It also explains how to use CNNs for medical image classification, segmentation and registration. Additionally, topics such as self supervised learning, generative adversarial networks and vision transformers will also be covered.
- This course provides unique knowledge on the application of deep learning to highly complex and non-standard (medical) problems (in 2D and 3D).
Tools you'll use
PythonSimpleITKNiBabelSlicer3DITKSnapFIJITensorFlowPyTorchKeras
Curriculum6 modules,
6 modules,
built with industry.
01Advanced Medical Image Processing
- Module 1 - Image SegmentationW01
- Motivation and Applications
- Image Segmentation
- Thresholding
- Energy Minimization Graph Cuts
- Active Contours
- Clustering
- Evaluating Segmentation Accuracy
- Module 2 - Image RegistrationW02
- Outline
- Modalities and Applications
- Image Registration
- Deformable Image Registration
- Optimization Approach
- Similarity Measures
- Module 3 - Convolutional Neural NetworksW03
- Overview of Machine Learning and Deep Learning Basics
- Theory of Convolutional Neural Networks (CNNs)
- Activation Functions
- Regularization
- Optimization
- Learning Rates
- Module 4 - Image Classification using CNNsW04
- CNNs for Classification
- CNN Building Blocks
- CNN Architecture
- Training Neural Networks
- Data Preprocessing
- Weight Initialization
- Training and Test Error
- Regularization
- Hyperparameters
- Medical Image Classification
- Module 5 - Image Segmentation using CNNsW05
- CNNs for Segmentation
- Sliding Windows
- Skip Connections
- Dilation
- FCN Architecture
- nnU-Net
- UNet Architecture
- Medical Image Segmentation
- Module 6 - Practical and Advanced TopicsW06
- Transfer Learning
- Self-Supervised Learning
- SSL for Medical Image Analysis
- FDA Regulations for Medical Image Analysis
- Module 1 - Image SegmentationW01
Industry projects1 projects
1 projects
you'll ship.
Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 1 Projects that are available in this program.
FeeOne fee.
One fee.
Everything included.
Become job ready with our comprehensive industry focused curriculum for freshers & early career professionals
Premium
₹40,000
Inclusive of all charges- 1 Year Access
- Personalized Page
- Live Individual & Group Sessions
- Personalized & Hands-On
- Job-Oriented Industry Relevant Curriculum
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Next stepNot sure it's
Not sure it's
the right fit?
A counsellor will walk you through the syllabus, projects and fee options — and tell you honestly if another course suits you better.