Embryo quality estimation from time lapse images for assisted reproduction

We have developed algorithms to classify embryo development stages from time lapse videos in order to extract timing information that can be used to predict genetic defects (aneuploidy). Now we want to add appearance and clinical information to improve the predictions.

We are looking for one PhD student and one postdoc.

Requirements: strong programming and research skills, prior experience with image processing and deep learning.

Leveraging expert knowledge for medical image segmentation

Despite recent advances, deep learning methods for medical image segmentation can be hampered by limited availability of expertly labeled data. This project proposes a novel approach to enhance segmentation quality by incorporating constraints on invariance, topology, dimensions, position, count, shape, and other segmentation properties. The method will also handle weak annotations like scribbles and global properties such as unbiasedness.

Our key objective is to develop efficient algorithms that integrate deep learning with constraint optimization techniques. We will investigate penalty, barrier, and projection methods, the moving target method and feasibility-guaranteeing reparameterization. These techniques will be coupled with transformation-invariant network operators.

We are looking for one PhD student and one postdoc.

Requirements: strong programming, mathematical and research skills, prior experience with image processing and deep learning.

Analysis of images in biology and medicine

I am constantly looking for new PhD students, post-docs, or experienced independent programmers for various projects concerning analysis of images in biology and medicine, for example histology slice registration or perfusion CT data processing. The candidates should have very good knowledge of programming, mathematics, image processing, and machine learning.