Medical Image Analysis Course | IIT Kharagpur | Prof. Debdoot Sheet
Course Details
| Exam Registration | 371 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 4 weeks |
| Categories | Electrical, Electronics and Communications Engineering |
| Credit Points | 1 |
| Level | Undergraduate/Postgraduate |
| Start Date | 16 Feb 2026 |
| End Date | 13 Mar 2026 |
| Enrollment Ends | 16 Feb 2026 |
| Exam Registration Ends | 27 Feb 2026 |
| Exam Date | 26 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Unlock the Future of Healthcare with Medical Image Analysis
The field of medical diagnostics and treatment is undergoing a revolutionary transformation, powered by advanced imaging technology and intelligent analysis. At the forefront of this revolution is Medical Image Analysis—a discipline that blends engineering, computer science, and medicine to extract life-saving information from medical scans. This burgeoning industry, projected to be worth billions, is creating unprecedented opportunities for engineers and technologists.
To equip the next generation of innovators, the prestigious Indian Institute of Technology Kharagpur (IIT Kharagpur) offers a focused, 4-week course designed and taught by a leading expert in the field. This course is your gateway to mastering the tools and techniques that are shaping modern medicine.
Meet Your Instructor: A Pioneer in Computational Medical Imaging
This course is led by Prof. Debdoot Sheet, an accomplished academic and innovator. As an Assistant Professor in the Department of Electrical Engineering at IIT Kharagpur and the founder of SkinCurate Research, Prof. Sheet brings a unique blend of deep academic knowledge and practical research experience.
His distinguished credentials include:
- MS and PhD from IIT Kharagpur in Computational Medical Imaging and Machine Learning.
- Experience as a DAAD visiting PhD scholar at the Technical University of Munich (TU Munich).
- Extensive publication record in top-tier journals like Medical Image Analysis (MedIA) and conferences such as the IEEE International Symposium on Biomedical Imaging (ISBI).
- Active membership in professional bodies including IEEE, SPIE, ACM, IUPRAI, and BMESI.
- Editorial role for IEEE Pulse since 2014.
His research spans deep learning, domain adaptation, surgical analytics, and augmented reality, ensuring the course content is both cutting-edge and highly relevant.
Course Overview: What Will You Learn?
This intensive 4-week program is structured to take you from the fundamentals to advanced applications, providing a complete overview of the medical image analysis pipeline.
Course Layout: A Step-by-Step Journey
| Week | Key Topics Covered |
|---|---|
| Week 1 | Introduction to medical imaging modalities (CT, MRI, Ultrasound, etc.) and essential image analysis software tools. |
| Week 2 | Core techniques for feature extraction and image segmentation, along with methodologies for systematic evaluation and validation on clinical datasets. |
| Week 3 | Application of Machine Learning and Deep Learning approaches for automated segmentation and disease classification tasks. |
| Week 4 | Practical case studies exploring recent advances in analyzing retinal images, CT scans, MRI, ultrasound, and histology slides. |
Who Should Enroll in This Course?
This course is meticulously designed for students and professionals aiming to build or transition into a career at the intersection of technology and healthcare.
Intended Audience & Prerequisites
- Level: Undergraduate and Postgraduate students.
- Categories: Ideally suited for students in Electrical, Electronics, Communications Engineering, Computer Science, and Biomedical Engineering.
- Prerequisite: A foundational knowledge of Digital Image Processing is required to fully grasp the advanced concepts.
Unlock Career Opportunities in High-Growth Industries
The skills you gain from this course are directly applicable in a wide array of leading industries. This course is supported by and relevant to major players in:
- Medical Imaging & Devices: GE, Siemens, Philips, Toshiba, Samsung, Zeiss, Aloka.
- Healthcare Software & Tech: Microsoft, Google, IBM, TCS, CDAC.
- Medical Technology Specialists: Robert Bosch, Boston Scientific, Volcano Corp., Rohde & Schwarz.
Whether you aspire to work on the next generation of imaging instruments, develop diagnostic AI software, or contribute to fields like medical robotics and augmented reality surgery, this course provides the essential knowledge base.
Why This Course is Essential for Your Future
Enrolling in this course is more than just an academic pursuit; it's an investment in a future-proof career. You will learn to:
- Translate engineering principles into solutions for real-world clinical problems.
- Develop and validate algorithms that can handle high-throughput data for clinical use.
- Gain hands-on insight into the complete workflow of medical image analysis, from data acquisition to diagnostic decision support.
Take the first step towards becoming a contributor to the multi-billion dollar medical imaging industry. Master the analytical skills that are critical for innovation in healthcare technology with expert guidance from IIT Kharagpur and Prof. Debdoot Sheet.
Enroll Now →