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You are here: Home / Resources / Teaching Materials / 3D breast cancer tissue reconstruction / Description
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3D breast cancer tissue reconstruction

Author(s): Jeremy M Wojdak1, Kerri-Ann Norton2

1. Radford University 2. Johns Hopkins University

311 total view(s), 159 download(s)

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Summary:
This module allows students to follow a researcher as she discovers new features of breast cancer tissue architecture, using 3D reconstructions of histological specimens.

Licensed under CC Attribution-NonCommercial-ShareAlike 4.0 International according to these terms

Version 1.0 - published on 24 Aug 2018 doi:10.25334/Q4899B - cite this Last public release: 2.0

Tags

  1. Audience Level
    1. High School
  2. Audience Level
    1. Undergraduate
      1. Introductory
  3. Audience Level
    1. Undergraduate
      1. Advanced
  4. Instructional Setting
    1. Lab
  5. graphing
  6. data visualization
  7. breast cancer
  8. DCIS
  9. histograms
  10. centroid
  11. sums of squares
Contents:
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Description

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:
Basic

  • 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.

Advanced/Extensions

  • Students will apply programming concepts to automate a series of procedures.
  • Students will quantify aspects of 3D shapes using image analysis.

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