Advanced Medical Image Processing
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Syllabus
This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects
Course Overview
- 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).
Course Syllabus
On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.
Module 1 - Image Segmentation
- Motivation and Applications
- Image Segmentation
- Thresholding
- Energy Minimization Graph Cuts
- Active Contours
- Clustering
- Evaluating Segmentation Accuracy
Module 2 - Image Registration
- Outline
- Modalities and Applications
- Image Registration
- Deformable Image Registration
- Optimization Approach
- Similarity Measures
Module 3 - Convolutional Neural Networks
- 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 CNNs
- 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 CNNs
- CNNs for Segmentation
- Sliding Windows
- Skip Connections
- Dilation
- FCN Architecture
- nnU-Net
- UNet Architecture
- Medical Image Segmentation
Module 6 - Practical and Advanced Topics
- Transfer Learning
- Self-Supervised Learning
- SSL for Medical Image Analysis
- FDA Regulations for Medical Image Analysis
Our courses have been designed by industry experts to help students achieve their dream careers
Industry Projects
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.
Full Scale Medical Image Analysis
- This project involves applying image registration, segmentation and classification to retinal images.
Our courses have been designed by industry experts to help students achieve their dream careers
Ratings & Reviews by Learners
Skill-Lync has received honest feedback from our learners around the globe.
Flexible Pricing
Talk to our career counsellors to get flexible payment options.
INR 40,000
Inclusive of all charges
Become job ready with our comprehensive industry focused curriculum for freshers & early career professionals
1 Year Accessto Skill-Lync’s Learning Management System (LMS)
Personalized Pageto showcase Projects & Certifications
Live Individual & Group Sessionsto resolve queries, Discuss Progress and Study Plans.
Personalized & Hands-OnSupport over Mail, Telephone for Query Resolution & Overall Learner Progress.
Job-Oriented Industry Relevant Curriculumavailable at your fingertips curated by Global Industry Experts along with Live Sessions.
Instructors profiles
Our courses are designed by leading academicians and experienced industry professionals.
1 industry expert
Our instructors are industry experts along with a passion to teach.
11 years in the experience range
Instructors with 11 years extensive industry experience.
Areas of expertise
- Artificial Intelligence
- Imaging technology
- Medical Imaging
- Biomedical Informatics
- Electrical Engineering
- Medical Image Processing
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