Within this project, we plan to establish an abstract description of common components of 3D vision data analysis workflows (DAWs) that allows for an efficient distribution on different computing hardware infrastructure as well as a simple adaptation to different experimental settings and sensors. The work includes the analysis, modularization and optimization of DAWs and vision algorithms with respect to computational and memory demands, scalability, data dependencies, and adaptability. The focus will initially be on three specific types of 3D vision / 3D reconstruction DAWs in the area of microscopy with visible light and high-energy electrons that are very diverse in their use of memory and data transfer rate, and suitable schemes of parallelization, namely optical reflection tomography of fossils captured in amber on a microscopic scale, 3D atomic-resolution electron ptychography in the transmission electron microscope, and real time tracking of microscopic FIB lamellae within a focused ion beam instrument.
High Resolution Three-Dimensional Reconstructions in Electron Microscopy Through Multifocus Ptychography Journal Article
In: Microscopy and Microanalysis, vol. 28, no. S1, pp. 364–366, 2022.
A three-dimensional reconstruction algorithm for scanning transmission electron microscopy data from a single sample orientation Journal Article
In: Microscopy and Microanalysis, vol. 28, no. 5, pp. 1632–1640, 2022.
Approaches Taken to Streamline and Consolidate Large Dataset Processing Techniques, with a Focus on Ptychography Journal Article
In: Microscopy and Microanalysis, vol. 28, no. S1, pp. 2994–2996, 2022.
Deep Reinforcement Learning for Data-Driven Adaptive Scanning in Ptychography Journal Article
In: arXiv preprint arXiv:2203.15413, 2022.
Lossy Compression of Electron Diffraction Patterns for Ptychography via Change of Basis Journal Article
In: arXiv preprint arXiv:2211.07372, 2022.