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Retinal vessel segmentation

Primary Investigators:
Ipek Oguz
Brief Description of Project:
OCT and OCT angiography methods allow us to image the retinal vascular perfusion, but due to the noisy nature of the images, it is challenging to reliably obtain quantitative measurements about the vessels. This project will focus on machine learning algorithms to automatically extract the vessels, and creating image annotations to be used for training the algorithms. I expect this project to lead to a submission to the SPIE Medical Imaging Conference by the end of the summer.

Desired Qualifications:
Nature of Supervision:
I will meet with the student weekly. I have additional meetings as needed (e.g., near conference deadlines, etc). Both me and the other senior lab members (grad students/postdocs) are available for more frequent help as needed. 

A Brief Research Plan (period is for 10 weeks):
1 week - project overview and plan development
6 weeks - project implementation
1 week - statistical evaluation
2 week - project write-up  

Number of Open Slots: 2
Contact Information:
Name: Ipek Oguz
Department: Electrical Engineering & Computer Science