Computing Imaging-Based Science

CMSC 34900-1 (Topics in Scientific Computing):
Computing Imaging-Based Science

Instructor:

Gordon Kindlmann

Class:

Wednesdays 2:30pm -- 5:30pm

Room 140 (Zar Room), Crerar Library

Office hours:

In Ryerson 161-B: Tuesdays 3-4:3pm, Thursdays 10am-noon

Quick links:

Description:

In many areas of experimental science, the acquisition and computational analysis of 2D, 3D, or 4D images is a necessary step in the scientific investigation. This class will cover concepts and methods of scientific image processing and analysis, in the context of real-world imaging data, from ongoing research on campus. In this offering of the class (Autumn 2013), datasets and driving scientific problems come mainly from research in biology and physics. Class has four components: readings on the image processing methods and applications, lectures to cover concepts and mathematical background, guest lectures by researchers to learn about the scientific context of the imaging, and programming exercises with datasets shared by the researchers.

Note: If you are taking this class to satisfy an elective requirement in the Computer Science department, you will need to propose (by roughly mid-quarter) and complete (by the end of the quarter) a programming project. The project proposal and submission will be done by arrangement with the instructor. The scope and difficulty of the project will have to be distinctly larger than that of the regular programming exercises.

Prerequisites

No specific classes are prerequisites, but:

You should know how to code. This means you can: use books and the web to learn a language and its features, build on and combine example programs, and debug methodically. We will be using a mix of C and Python in this class.
Your math background should include linear algebra and calculus.

Communication and Resources

Readings: There is no single textbook. There will be readings from chapters in textbooks, and papers in the image processing and scientific literature. Readings will distributed via the cibs-2013 SVN repository.
Web: The class web page at http://people.cs.uchicago.edu/~glk/class/CIBS/ will list readings and programming exercises.
Email: Registered students will be subscribed to the class mailing list with their CNetID@uchicago.edu address. Consult the the list archives as needed. The password to manage your mailing list membership is included in the initial message (with subject: Welcome to the "Cibs-2013" mailing list) you get upon joining the list.
SVN: The SVN for CIBS page describes how svn will be used for getting data and other files, and for handing in work.
The Software for CIBS page describes what software is required to do the programming assignments. The RCC Linux computers will have the required software installed, but you are welcome to get things working on your own computer as well (the instructor may or may not be able to help with this).

Grading

Grades are assigned according to class attendence and participation in discussion about the assigned readings (50%), and satisfactory completion of the programming exercises (50%). The point of the programming exercises is not to do extensive software development, but to maintain a tangible connection to how the methods are actually implemented. There are no exams.

Syllabus

Each week of the course is expected to cover the following material. The first half of the course covers mathematical fundamentals and the methodological underpinnings of the image analysis methods used by the scientists. The second half goes into detail on specific applications, including a presentation from a scientist to describe the research context of the image data acquisition, the analysis questions that are asked of the data, and the methods used to answer those questions.