Carnegie Mellon University

Bioimage Informatics

Course Number: 02-740

With the rapid advance of bioimaging techniques and fast accumulation of bioimage data, computational bioimage analysis and modeling are playing an increasingly important role in understanding of complex biological systems. The goals of this course are to provide students with the ability to understand a broad set of practical and cutting-edge computational techniques to extract knowledge from bioimages.

Upon successful completion of this course, the student will be able to:

  • explain the importance and understand the principles and uses of both geometrical and machine learning-based bioimage analysis techniques
  • understand how these techniques can be combined for various applications
  • develop code to implement basic techniques
  • solve specific bioimage analysis tasks using image-processing libraries

Units: 12
Prerequisite(s): 10301 or 10315 or 02620 or 10701 or 10601. Students are expected to have some experience with programming in python.

Assessment Structure: 

Coursework will include homework, two in-class examinations, and doing an independent project on a practical bioimaging problem.