Medical Image Analysis
Learn about diagnostic medical images through advanced algorithms and deep-learning techniques with the Medical Image Analysis certification by NPTEL.
Online
12 WeeksQuick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The Medical Image Analysis certification course delves into automated analysis techniques for diagnostic medical images, such as X-rays, CT scans, and MRI scans. It targets undergraduates and postgraduates with a foundation in calculus, linear algebra, introductory optimisation, and matrix computations. Participants learn image visualization, processing, segmentation, and registration
With the Medical Image Analysis certification by NPTEL, students engage in practical demonstrations and case studies, honing their skills in computer-aided diagnosis. They emerge equipped to apply sophisticated techniques in real-world scenarios, making them sought-after professionals in the field and appealing to diagnostic imaging companies seeking expertise in automated medical image analysis.
Also Read: Online Medical Imaging Certification Courses
The Highlights
- Online Course
- 12 Weeks Duration
- Offered by IIT Madras
Programme Offerings
- Certificate of completion
- Practical Learning
- Hands-on Experience
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIT Madras (IITM) |
Eligibility Criteria
Academic Qualifications
You need to know calculus, linear algebra, basic optimisation, and introductory matrix calculations before taking the Medical Image Analysis certification course.
Certification Qualifying Details
To receive the Medical Image Analysis certification by NPTEL, you need a minimum average assignment score of 10/25 and an exam score of 30/75.
What you will learn
After completing the Medical Image Analysis certification syllabus, you will acquire a comprehensive understanding of automated analysis techniques tailored specifically for diagnostic medical images, including X-rays, CT scans, and MRI scans. You will also delve into various aspects of image processing, segmentation, and registration.
Upon completion of the Medical Image Analysis training, you will explore image visualization, interpretation of the resolution, and basic image processing techniques. You will also learn image segmentation and registration techniques, both with rigid and non-rigid models.
Who it is for
The Medical Image Analysis online course suits individuals interested in diagnostic medical images, particularly those with a background in calculus, linear algebra, introductory optimisation, and introductory matrix computations. This course can also be beneficial for:
- Clinicians
- Research Scientists
- Biomedical Engineers
- Machine Learning Engineers
Admission Details
Follow these steps to join the Medical Image Analysis classes:
Step 1: Browse the URL below: https://swayam.gov.in/NPTEL.
Step 2: Click on the “Sign-in/ Register” button.
Step 3: Log in using a Google account-enabled email address.
Step 4: Select your preferred course. Review the course details and fill out the required fields.
Step 5: Click on the "Join" button.
The Syllabus
- Introduction to medical imaging
- Basic image processing techniques
- Image registration – 1- Rigid models
- Image registration – 2- Non-Rigid models
- Image registration – 3- Application and demonstration
- Image segmentation - Statistical shape model
- Image segmentation – PDE based methods
- Image segmentation – application and demonstration
- Computer Aided Diagnosis – Case Study 1
- Computer Aided Diagnosis – Case Study 2
- Deep Learning for Medical image analysis – 3D Convolutional Neural Networks
- Deep Learning for Medical image analysis – Generative models for synthetic data
Evaluation process
The Medical Image Analysis certification offers an optional exam. Your final score is determined by averaging the best 8 out of 12 assignments (25%) and your proctored exam score (75%).
Instructors
IIT Madras (IITM) Frequently Asked Questions (FAQ's)
You should have a basic understanding of calculus, linear algebra, introductory optimisation, and introductory matrix computations.
The course includes practical demonstrations and case studies, enabling you to apply the learned techniques to real-world medical image analysis tasks.
While some familiarity with the basics of medical imaging is helpful, the course covers fundamental concepts and progressively advances to more advanced topics, making it accessible to beginners.
The course includes dedicated weeks focusing on deep learning techniques, particularly 3D convolutional neural networks and generative models for synthetic data in medical imaging.
You will be equipped with valuable skills sought by diagnostic imaging companies, making you eligible for roles such as medical imaging scientist, biomedical engineer, or machine learning engineer in healthcare.