Few Shot Segmentation in Medical Imaging
Supervision: Prof. Dr. Nassir Navab,
Dr. Shadi Albarqouni,
Ari Tran
Abstract
Semantic segmentation does a pixel-wise classification to assign a class or background to each pixel of an image. This problem requires a very large data set of pixel level annotations, which is often unavailable or very costly to create. The aim of this project is to build a state of the art low shot deep learning technique for medical images, which can from few dense or sparse annotated medical image labels derive semantic segmentation of a new previously unseen class.
Requirements:
- Good understanding of statistics and machine learning methods.
- Very good programming skills in Python & TensorFlow? / PyTorch?
Location: