@Book{1982199067,
author="Trelin, Andrii",
title="Imaging and motion detection at the nanometer scale: a data-driven approach",
year="2024",
address="Germany; Rostock",
abstract="This thesis applies data-driven methods to small signal detection in physics, focusing on optical sensing of neuron action potentials and nanoscale tomography of nitrogen-vacancy centers in diamonds. It introduces ChiSCAT, an optical scheme and algorithm that recover membrane motion signals from non-image data, validated on human cells and shared as open datasets. It also presents an optimized NV tomography method that cuts acquisition time by {\~}10x. These results show how advanced data processing can unlock signals from challenging measurements, bridging data science and experimental physics.<eng>",
school="Universit{\"a}t Rostock",
note="vorgelegt von Andrii Trelin",
note="Enth{\"a}lt Zeitschriftenartikel",
note="GutachterInnen: Dmitry Postnov (Aarhus University) ; Oliver Otto (Universit{\"a}t Greifswald)",
note="Dissertation Universit{\"a}t Rostock 2025 Kumulative Dissertation",
doi="10.18453/rosdok_id00005764",
url="https://purl.uni-rostock.de/rosdok/id00005764",
url="https://nbn-resolving.org/urn:nbn:de:gbv:28-rosdok_id00005764-1",
url="https://d-nb.info/1418060054/34",
url="https://doi.org/10.18453/rosdok_id00005764",
language="English"
}