| Abstract [eng] |
This master thesis presents the development of the miEye, a bench-top cost-effective super-resolution single-molecule localization microscope, and the accompanying microEye Python package for hardware control, data acquisition, and analysis. The miEye utilizes industrial CMOS cameras with thermoelectric and water cooling to achieve high signal-to-noise ratio for single-molecule detection. The optimal industrial CMOS camera is identified using a dark calibration method to estimate detectors' gain, dark current, baseline, read noise, and thermal noise. The performance of miEye is benchmarked using commercially available DNA-PAINT nano-rulers sample, and the lateral sample drift and resolution are assessed. The miEye's performance in dSTORM imaging of nuclear pore complexes is also evaluated. The aim of this work is to design and build an open-source bench-top super-resolution SMLM platform using cost-effective equipment, identify the optimal industrial CMOS camera, benchmark the performance of miEye, assess its performance in dSTORM imaging of nuclear pore complexes, and create a robust platform for miEye using the Python open-source package microEye. |
