Cross-Domain Translation of Angiography: From Stenosis to Healthy Vessel Appearance

Overview

• Optimal stent choice is essential for optimal long-term therapy outcome

• Knowing the original size and shape of a diseased vessel can support the optimal stent choice

• Development of an unsupervised learning framework for data domain transfer from diseased to healthy vessel

  • E.g. with a cycle GAN

• For coronary and/or iliac angiography data

Skills

• Python programming experience (keras or pytorch, scikit, pandas, numpy,…)

• Deep Learning knowledge (CNN, GAN)

• Image processing knowledge

• Basic medical or anatomy knowledge is a plus

Tasks

• Literature research

• Data preparation and pre-processing pipeline implementation

• Probabilistic segmentation and/or detection model implementation, training and evaluation