About the WorkshopTo help diagnosis, therapeutic planning and follow-up, and biomedical research, medical image computing involves development of mathematical and computational algorithms for reliable, automated, quantitative analysis of medical imaging data.
It is necessary to use model-based approaches in medical image computing tasks that take into account prior knowledge. These models provide parameters to account for object appearance variability, making it possible to structure the image analysis problem as an optimization problem in search of the model parameters that best explain the image data. Different techniques exist based on the model's representation of choice. One popular choice is machine learning/artificial intelligence, which provides the ability to learn appropriate models directly from existing (curated) data. The workshop will provide wonderful opportunity to interact and network with academics, clinicians and experts from industry. The workshop is open to the researchers and students working in the area of medical imaging. |
WHO CAN APPLY? |
This workshop brings together researchers (early/established) that work in the area of medical image computing to provide comprehensive overview along with necessary tutorials to advance the important interdisciplinary area of medical image computing. This workshop will also have a poster session from the early career researchers (Ph.D. students/Post-Docs) to seek feedback from the experts of the field. Exceptional master students will also be selected as participants.
Note that accommodation expenses based on sharing basis will be taken care by the organizers depending on availability. |
Best Poster Awards:
Mr. Naveen Paluru
Mr. Yash Dravid Sachin
Ms. Ayantika Das
Mr. Vaddadi Venkatesh
Speakers!!!
Tentative List