WnCC - Seasons of Code
Seasons of Code is a programme launched by WnCC along the lines of the Google Summer of Code. It provides one with an opprtunity to learn and participate in a variety of interesting projects under the mentorship of the very best in our institute.
List of Projects
- Emoji Predictor
- FAQ Bot for Freshmen
- Capturing semantic structures in Neural Machine Translation
- Automated Fiducial Localisation from MRI/CT Images
- 3D Object Reconstruction from Single Image
- Statistical Modelling of Star Maps
- Face Recognition Systems
- Competitive Coding
- Can Machines Identify Genres?
- Monte Carlo Path Tracing Renderer
- Joint Modelling of Source Code and Natural Language
- Panorama in Cam Scanner
- Front end development for FOSSEE websites
- Institute Delivery System
- Capture The Swag
- Panorama in Cam-Scanner
- Poisson Solver with Image Editing
- Blind Source Separation
This project aims to automate the marking of the fiducials (bone based markers) in MRI/CT scan images.
Image-guided neurosurgery systems (IGNS) play an important role in intracranial surgery. These systems have a live CT/MRI scanning during surgeries to aid the doctor. During neuro-registration, bone based markers or fiducials are affixed to the skull before imaging so that they can calibrate the coordinate systems of the imaging device and the actual 3D World Coordinates. As of now, the actual Fiducials are tapped by instruments, and on the other hand they are MANUALLY marked out in the images obtained from the MRI/CT imaging. Automatic localization of these centers will help to reduce the human error in registration and speed up the registration process. In a nutshell, the task is to automatically locate these Fiducial markers from these images, so that they don’t have to be manually marked out by the doctor.
This project was a research challenge provided by scientists working in BARC (Bhabha Atomic Research Centre), during the Inter IIT Tech Meet, 2017 held at IITM. We came second, after developing an algorithm which worked quite well. We believe it can be further worked upon to work extremely well. This task is still open, and scientists in India are actively looking for a solution. Also, we found very little literature on this task, and aim to publish this work too.