UNM Physics 480/501: Julia for Microscopy Image Analysis

480 CRN: 31448
501 CRN: 31449
Dates: June 3 – July 30, 2024
Days: M Tu W
Time: 9:00 – 10:40
Location: PAIS 1160
Instructor: Prof. Keith Lidke
Office: PAIS 2418
Email: klidke@unm.edu
Course GitHub Organization: Julia4Microscopy2024

Office Hours

After class, anytime you can find me in my office, or by appointment.

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Overview

This course is targeted to graduate students (501) or upper-division undergraduate students (480) who will use the Julia Language in their research. The examples and focus of the course will be on topics related to biological imaging using microscopy, however many topics are of general interest to anyone wanting to learn more about the Julia programming language. The course can be taken for 1, 2, or 3 credits. The division of content is shown below. This will be an in-person, hands-on course that will include many interactive programming and image analysis sessions. Students must bring a laptop computer to class.

Prerequisites

Students are assumed to be proficient in at least one programming language (e.g., MATLAB, Python, Julia). No time will be spent on basic programming concepts. Students are also assumed to have working knowledge of calculus, differential equations, and linear algebra and have a conceptual understanding of Fourier transforms/analysis. No prior background in microscopy or biology is assumed.

The course will progress through the following topics:

• Git, GitHub and Continuous Integration software development
• Julia environments and package development
• Multiple Dispatch
• Use of AI Tools (e.g., GitHub Copilot, LLMs)
• Jupyter Notebooks, Interactive Plotting, Animations
• Curve Fitting and Optimization
• Multidimensional Data and Images
• Segmentation and Transformations
• Deconvolution
• Image Registration and Stitching
• Image and Data storage formats
• GPUs: Array and Kernel programming
• Deep Learning and Convolution Neural Networks
• Topics from Super-resolution, Single Particle Tracking, and Lightsheet microscopy

Color indicates the breakdown of topics that will be covered for 1,2 or 3 credits.