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Medical image analysis

Primary Investigators:
Ipek Oguz
Brief Description of Project:
Medical image analysis is a vibrant field of research that involves many computer science skills such as machine learning/deep learning and computer vision. Examples include tasks like identifying the boundaries of various brain structures in an MRI scan, computationally enhancing the quality of a noisy ultrasound scan, or training neural networks to predict patient outcomes from images. We have a number of applications (different imaging types, different body parts, different computational tasks) we are working on within this context; the specific tasks for the internship will be determined to match the skills and interest areas of the intern(s). Ideally, internship projects are expected to lead to a submission to the SPIE Medical Imaging Conference by the end of the summer.

Desired Qualifications: 
- At least one of C++ or Python programming is required. 
- Familiarity with PyTorch or TensorFlow is additionally helpful. 
- No prior medical knowledge is needed. 

Nature of Supervision:
A Brief Research Plan (period is for 10 weeks):
1 week - project overview and plan development
7-8 weeks - project implementation
1-2 weeks - project write-up 

Number of Open Slots: 3
Contact Information:
Name: Ipek Oguz
Department: Electrical Engineering and Computer Science