Joint Iterative Reconstruction and Motion Compensation for Optical Coherence Tomography Angiography

• Applicant: Professor Dr.-Ing. Andreas Maier
• Subject Area: Medical Informatics and Medical Bioinformatics ; Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing ; Medical Physics, Biomedical Technology
• Term: from 2019 to 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 414781207

While OCTA imaging has shown great promise for improving patient care in ophthalmology, its full potential has been limited. There is an urgent need for robust and accurate motion detection and correction and improved OCTA processing algorithms that will decrease noise levels and improve image quality and resolution. Furthermore, there is only few open-source software that enables researchers from around the world to produce high quality images. In order to address these needs, the project will pursue the following objectives:A) Improved motion compensation including the use of the OCTA signal for improved data consistency, more accurate motion models that allow affine motions such as rotation and scaling, and integration of surrogate signals stemming from camera-based eye-tracking or navigator-based motion estimation approaches yielding a full 3-D correction for all acquired A-scan data.B) Physically correct OCTA signal extraction that employs compressive sensing-based regularization approaches in the OCTA signal extraction and integrates the full 3-D motion model from Objective A including the interpolation process in combination with correct physical noise models.C) Precision Learning Reconstruction that augments the physically correct model from Objective B with additional deep learning techniques to learn data-optimal sparse domains and optimal navigator patterns for motion signal extraction.All software created in this project will be published as open source software.

• DFG Programme: Research Grants