BIOMEDICAL IMAGE ANALYSIS

Prerequisites & course information

Requisites: ( MATH 320 , 340 , 341 , 345 , or 375 ) and (STAT 511, 541 , POP HLTH/B M I 551 , MATH 331 , MATH/STAT 431 , 309 , STAT 240 , 301 , 311 , 324 , 371 , or STAT/F&W ECOL 571 , or HORT 571 prior to Spring 2025) or graduate/professional standing Course Designation: Core GenEd - Natural Science & Wellness Breadth - Natural Science Level - Advanced L&S Credit - L&S Liberal Arts and Science Repeatable for Credit: No Last Taught: Spring 2026 Learning Outcomes: 1. Implement the key principles of ideas from probability, statistics and computer vision algorithms used in medical image analysis Audience: Undergraduate 2. Recognize which image analysis problems will benefit from which modeling approach Audience: Undergraduate 3. Apply algorithms about image analysis tasks and implement algorithms and pipelines using a programming language Audience: Undergraduate 4. Implement the building blocks taught in this course to independently learn and apply new, but related imaging analysis algorithms Audience: Undergraduate Learning Outcomes: 1. Implement the key principles of ideas from probability, statistics and computer vision algorithms used in medical image analysis Audience: Undergraduate 2. Recognize which image analysis problems will benefit from which modeling approach Audience: Undergraduate 3. Apply algorithms about image analysis tasks and implement algorithms and pipelines using a programming language Audience: Undergraduate 4. Implement the building blocks taught in this course to independently learn and apply new, but related imaging analysis algorithms Audience: Undergraduate