Analyzing Images to learn Mathematics and Statistics
3D breast cancer tissue reconstruction
We are all inundated with news stories of the results of cancer research, but few students (or faculty) will have any tangible experience seeing or doing that kind of research themselves. This module allows students to follow a researcher as she discovers new features of breast cancer tissue architecture, using 3D reconstructions of histological specimens.
This module was created as a way to get students thinking in new quantitative ways using cutting edge breast cancer research as the context for discovery, letting students experience the utility of math in science first-hand. Students follow along with a simplified but realistic approximation of the original research by reconstructing tissues in 3D to test predictions from a mechanistic agent-based model. There are several quantitative "side trips" that instructors can elect to include/exclude, that expose students to mathematical ideas used to automate image analyses. No prior instructor experience in these topics is assumed or necessary.
Potential Learning Objectives:
Students will be able to use sums of squares to describe differences.
Students will use image analysis software to generate data from an image set.
Students will use image analysis software to generate a 3D data visualization from an image set.
Students will be able to construct and interpret frequency histograms.
Students will gain appreciation for the interplay between modeling and empirical work.
Students will gain appreciation for the utility of mathematics and computation for biology and medicine.
Students will write a discussion section in typical scientific literature format.
Students will apply programming concepts to automate a series of procedures.
Students will quantify aspects of 3D shapes using image analysis.