Global ETD Search

1	A Task-Specific Approach to Computational Imaging System Design Ashok, Amit January 2008 (has links) The traditional approach to imaging system design places the sole burden of image formation on optical components. In contrast, a computational imaging system relies on a combination of optics and post-processing to produce the final image and/or output measurement. Therefore, the joint-optimization (JO) of the optical and the post-processing degrees of freedom plays a critical role in the design of computational imaging systems. The JO framework also allows us to incorporate task-specific performance measures to optimize an imaging system for a specific task. In this dissertation, we consider the design of computational imaging systems within a JO framework for two separate tasks: object reconstruction and iris-recognition. The goal of these design studies is to optimize the imaging system to overcome the performance degradations introduced by under-sampled image measurements. Within the JO framework, we engineer the optical point spread function (PSF) of the imager, representing the optical degrees of freedom, in conjunction with the post-processing algorithm parameters to maximize the task performance. For the object reconstruction task, the optimized imaging system achieves a 50% improvement in resolution and nearly 20% lower reconstruction root-mean-square-error (RMSE ) as compared to the un-optimized imaging system. For the iris-recognition task, the optimized imaging system achieves a 33% improvement in false rejection ratio (FRR) for a fixed alarm ratio (FAR) relative to the conventional imaging system. The effect of the performance measures like resolution, RMSE, FRR, and FAR on the optimal design highlights the crucial role of task-specific design metrics in the JO framework. We introduce a fundamental measure of task-specific performance known as task-specific information (TSI), an information-theoretic measure that quantifies the information content of an image measurement relevant to a specific task. A variety of source-models are derived to illustrate the application of a TSI-based analysis to conventional and compressive imaging (CI) systems for various tasks such as target detection and classification. A TSI-based design and optimization framework is also developed and applied to the design of CI systems for the task of target detection, it yields a six-fold performance improvement over the conventional imaging system at low signal-to-noise ratios. optical PSF engineering joint optimization phase mask task specific information degrees of freedom computational imaging
2	Tomographic STED Microscopy Krüger, Jennifer-Rose 22 February 2017 (has links) No description available. 530 Physik (PPN621336750) Fluorescence microscopy Superresolution techniques STED microscopy PSF engineering Biophysics Cell imaging
3	Adaptive Scanning for STED Microscopy Vinçon, Britta 31 January 2020 (has links) No description available. 530 Physik (PPN621336750) STED microscopy adaptive scanning low light dose PSF engineering fluorescence microscopy super-resolution techniques biophysics cell imaging
4	Vision Beyond Optics: Standardization, Evaluation and Innovation for Fluorescence Microscopy in Life Sciences Huisman, Maximiliaan 01 April 2019 (has links) Fluorescence microscopy is an essential tool in biomedical sciences that allows specific molecules to be visualized in the complex and crowded environment of cells. The continuous introduction of new imaging techniques makes microscopes more powerful and versatile, but there is more than meets the eye. In addition to develop- ing new methods, we can work towards getting the most out of existing data and technologies. By harnessing unused potential, this work aims to increase the richness, reliability, and power of fluorescence microscopy data in three key ways: through standardization, evaluation and innovation. A universal standard makes it easier to assess, compare and analyze imaging data – from the level of a single laboratory to the broader life sciences community. We propose a data-standard for fluorescence microscopy that can increase the confidence in experimental results, facilitate the exchange of data, and maximize compatibility with current and future data analysis techniques. Cutting-edge imaging technologies often rely on sophisticated hardware and multi-layered algorithms for reconstruction and analysis. Consequently, the trustworthiness of new methods can be difficult to assess. To evaluate the reliability and limitations of complex methods, quantitative analyses – such as the one present here for the 3D SPEED method – are paramount. The limited resolution of optical microscopes prevents direct observation of macro- molecules like DNA and RNA. We present a multi-color, achromatic, cryogenic fluorescence microscope that has the potential to produce multi-color images with sub-nanometer precision. This innovation would move fluorescence imaging beyond the limitations of optics and into the world of molecular resolution. microscopy nanoscopy fluorescence cryogenic cryo-fluorescence cryoFM FM 3DSPEED SPEED standardization PSF PSF engineering achromatic dichroic multi-color super-resolution imaging imaging standard optics adaptive optics meta-data meta MetaMax calibration characterization back-projection image reconstruction pseudo-tomography model-based reconstruction chromatic aberrations cryogenic imaging 4D-PSF calibration tool Bioimaging and Biomedical Optics Biological Engineering Biomedical Devices and Instrumentation Biophysics Computer-Aided Engineering and Design Electrical and Electronics Electromagnetics and Photonics Electro-Mechanical Systems Engineering Physics Molecular Biology Nanoscience and Nanotechnology Numerical Analysis and Computation Optics Other Engineering Systems and Integrative Engineering

1

Page generated in 0.0796 seconds