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Lecturer(s)
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Tůma Roman, prof. Mgr. Ph.D.
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Course content
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1) Seeing is believing: What is light and how can it help us understand nature - the objective of optical imaging, examples of use 2) Optical setups and principles of image formation - light sources, optical components, microscopy, beams, ray and Fourier optics, interference 3) Detection of light - quantum nature of light, single point and array detectors, cameras, sensors, time resolution and sensitivity 4) Light microscopy - types of microscopes and illumination, beam steering and scanners, sample stages and environmental chambers, transmission, fluorescence, reflection, interference, phase contrast, Nomarski optics etc., magnification, field of view 5) Refractive index imaging and holography - principles and practice - Nanolive live cell imaging 6) Fluorescence microscopy - epifluorescence, confocal, total internal reflection (TIR), live cell imaging in different modes - examples and demonstrations, advantages and common drawbacks 7) FRET, lifetime and correlative imaging - FLIM, FCS, RICS and other fluorescence fluctuation techniques 8) Super-resolution imaging - single molecule detection, PALM and STORM (demonstration and image processing), structured illumination, STED 9) Single molecule tracking - principles and implementation including cell biology requirements and protocols, image processing 10) Spectral imaging- Raman and infrared - examples of analysis and use in cell biology 11) Non-linear spectroscopic methods - 2 photon excitation fluorescence, CARS 12) Practical image processing and analysis of time-resolved (4D) data sets
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Learning activities and teaching methods
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Demonstration, Laboratory, E-learning, Work with multi-media resources (texts, internet, IT technologies), Blended learning
- Preparation for exam
- 40 hours per semester
- Class attendance
- 21 hours per semester
- Preparation for classes
- 20 hours per semester
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Learning outcomes
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Provide students with working practical knowledge of optical microscopy and its principles, and associated image processing.
Learning outcomes: 1) Understand geometrical (paraxial) optics and use it to design, build, align and test simple imaging setup. 2) Understand Fourier optics and use its software implementation in Matlab to describe light propagation and image formation through a simple setup. 3) Understand basics of optical microscopes, different illumination types, magnification, numerical aperture, relay lenses, and common aberrations and resolution limitations. 4) Understand how contrast is formed under different illumination, image formation and acquisition using cameras and point detectors and their basic parameters (sensor and pixel size, noise sources, sensor types, readout speed and noise, quantum efficiency). 5) Understand light coherence and propagation of laser (Gaussian) beams and their use in optical coherence tomography and holographic microscopes 6) Understand fluorescence microscopy and its practical implementation (laser/LED excitation, filters, dichroics) and use in different formats: TIRF, confocal, wide-field, single molecule imaging 7) Using time domain in imaging: time-lapse, FLIM, FRAP, FCS, RICS 8) Understand basics and use of spectral imaging by fluorescence spectroscopy (including FRET and ratio imaging) and Raman (vibrational) spectroscopy 9) Understand different ways how to surpass the diffraction resolution limit, i.e. principles of super-resolution microscopy: single molecule localization, structured illumination, STED 10) Being able to acquire images and videos on various platforms available in the local labs 11) Appreciate the relevant requirements of life cell imaging and biological sample preparation, such as proper imaging media, temperature, gas composition, cell imaging chambers, staining, labelling and fixation. 12) Being able to process and interpret images/movies in ImageJ/Fiji 13) Being able to design an imaging experiment to answer a specific question, including image processing, quantification, and interpretation.
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Prerequisites
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Basic physics and optics (undergraduate), basic optical spectroscopy, working knowledge of computers-e.g. being able to install and learn how to use software packages (OpticalRayTracer, Matlab, Fiji), strong motivation to solve problems independently. Reasonable level of English is requred.
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Assessment methods and criteria
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Seminar work, Development of laboratory protocols, Interim evaluation
Assessment: 1) 60% is allocated to in course assessment of independent problem solving, data processing, writing up lab reports and answering questions related to the reading assignments and self-study. Passing criteria are: Submitting 80% assignments on time, each with minimum 40% score. Failure may be remedied by additional work, depending on circumstances and at the discretion of the module manager. The remaining 40% is allocated to a final take-home exam (seminar work) which will encompass design of imaging experiment and software driven image processing and quantification, submitted in a form of short report. Passing grade 60% of maximum points.
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Recommended literature
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On line library in Teams class.
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Petr Malý. Optika (Karolinum 2013).
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