Course Catalogue

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This course will cover the Physics of image propagation, including Fourier beam propagation, and use this to understand advanced techniques such as Ptychography and Point Spread Function engineering, where the image recorded on a camera requires further processing to reveal an image of the sample. Lectures and practical classes will enable students to engage with modern image reconstruction techniques including deconvolution and phase retrieval.

There will be 9 one-hour lectures on campus, each accompanied by a 3 hour practical class in a computer cluster.

This course requires a strong background in mathematics and is thus a core course only for the "Physical Sciences (PS)" track of the associated International Masters programme. This corresponds to an undergraduate degree in Physics, Computer Science, or appropriate Engineering disciplines.

None

A one hour written exam will assess conceptual understanding of the course, and provide students with an opportunity to demonstrate their grasp of the mathematical details in exam conditions, worth 40%.

Four lab reports, submitted as Jupyter notebooks including text and mathematics as well as code and outputs will contribute 10% each of the final mark, i.e. 40% in total.

Two oral assessments of the two highest-scoring lab reports will test authorship and understanding of the submitted lab reports, worth 10% each, total 20%.

The course aims to provide students with an in-depth understanding of computational microscopy, focusing on both theoretical principles and practical applications. Through a combination of lectures, computational labs, and practical sessions, students will gain proficiency in fundamental concepts such as image formation, deconvolution, point spread function engineering, resolution quantification, 3D information recovery, phase retrieval, digital holography, and Fourier Ptychography. The content is aligned with current research in Imaging Concepts and Optics, ensuring relevance and applicability to cutting-edge developments in the field. The course structure is designed to facilitate active learning and hands-on experience. This course is suitable as a core course for students in the PS track while also accessible to students with the requisite skills from other disciplines.

By the end of this course students will be able to:

■ Demonstrate a solid understanding of the basic principles of image formation, including concepts such as Point Spread Function (PSF), spatial frequencies, and Modulation Transfer Function (MTF), enabling them to tackle advanced problems in computational microscopy.

■ Apply advanced deconvolution and point spread function engineering techniques to enhance resolution and contrast in computational microscopy images, thereby improving the quality of images acquired for research projects.

■ Implement and optimize the Richardson-Lucy algorithm for image restoration, enabling effective and efficient restoration of degraded images in research projects.

■ Quantify image resolution using various methods such as test targets, knife-edge analysis, and Fourier Ring Correlation, facilitating accurate evaluation of image quality and resolution in research applications.

■ Retrieve three-dimensional information from multiple views in computational microscopy, allowing for advanced three-dimensional analysis of image data to obtain detailed insights into sample structure and morphology.

■ Apply phase retrieval techniques, including the Gerchberg-Saxton algorithm, to retrieve phase information from image data, which is essential for certain microscopy applications.