Medical Image Analysis

By Prof. Ganapathy krishnamurthi | IIT Madras

Learners enrolled: 1850

About the course: This course deals with automated analysis of diagnostic medical images, namely X-rays, CT and MRI scans. We will start with some basic material on how to visualize medical images and how to interpret the resolution of medical images correctly in addition to standard techniques for image processing. In successive weeks we will examine often used and powerful algorithms for image segmentation and image registration. We will then look at how these automated methods can be used to enable computer aided diagnosis. In the final 2 weeks, we will discuss deep learning for medial image analysis , especially state of the art 3D convolutional neural networks.

PRE-REQUISITES: Knowledge of calculus, Linear Algebra, introductory optimization and introductory matrix computations
INTENDED AUDIENCE: UG/PG
INDUSTRY SUPPORT: Any diagnostic imaging company will be interested.

Summary

Course Status :	Completed
Course Type :	Core
Language for course content :
Duration :	12 weeks
Category :	Biological Sciences & Bioengineering
Credit Points :	3
Level :	Undergraduate/Postgraduate
Start Date :	25 Jul 2022
End Date :	14 Oct 2022
Enrollment Ends :	08 Aug 2022
Exam Date :	29 Oct 2022 IST

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1: Introduction to medical imaging

Week 2: Basic image processing techniques

Week 3: Image registration – 1- Rigid models

Week 4: Image registration – 2- Non-Rigid models

Week 5: Image registration – 3- Application and demonstration

Week 6: Image segmentation - Statistical shape model

Week 7: Image segmentation – PDE based methods

Week 8: Image segmentation – application and demonstration

Week 9: Computer Aided Diagnosis – Case Study 1

Week 10: Computer Aided Diagnosis – Case Study 2

Week 11: Deep Learning for Medical image analysis – 3D Convolutional Neural Networks

Week 12: Deep Learning for Medical image analysis – Generative models for synthetic data

Instructor bio

Prof. Ganapathy krishnamurthi

IIT Madras

Prof. Ganapathy Krishnamurthi is now an Associate Professor in the Department of Engineering Design at IIT-Madras. His research work is primarily in the area of medical image analysis and image reconstruction.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.

The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).

Date and Time of Exams: 29 October 2022 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.

Registration url: Announcements will be made when the registration form is open for registrations.

The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.

Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.

Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Madras. It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team