Machine Learning for Biological and Medical Imaging


Project Description

We have recently developed hybrid machine learning techniques for retinal images. For publications see google scholar( Challenges include limited number of images, unbalanced data-sets, and interpretability of feature representations. Subprojects include to

Formulation and training of robust generative models (e.g.GANsand versions thereof) for the Retinal Dataset-

Extend and apply the techniques to melanoma datasets Develop and apply techniques to identify meaningful (biological/medical) feature representation from a successfulclassification

Program - Computer Science
Division - Computer, Electrical and Mathematical Sciences and Engineering
Field of Study - ​Computer Science, Applied Mathematics

About the

Jesper Tegner

Jesper Tegner

Desired Project Deliverables

​Individual projects will be tailored and narrowly designed from the above palette according to interest of the student, technical proficiency, and level of study. We expect you(a)tobringenthusiasm,creativity,andhardwork,(b)givelabseminarsonyourwork, and (c) produce a final written report.In returnthis facilitates your critical thinking, presentations skills, and scientific writing.Yourresearch, in collaboration and with support of team members, may lead to scientific publications. You will also get a good hands-on perspective at the frontier of machine intelligence and its applications in an interdisciplinary research group andenvironment​.