ENGG 113 - Image Visualization and Analysis

Description

The goal of this course is to introduce graduate level and senior undergraduate students who are working in imaging research to image processing and visualization in 3D using advanced libraries and fully functional software development framework. The most widely used open source software tools for medical image analysis and visualization will be used as the platform: The Insight Registration Segmentation Toolkit (ITK), the Visualization Toolkit (VTK), OpenCV, Qt, and CMake. ITK is an open-source, widely adopted, cross-platform system that provides developers with an extensive suite of software tools for image analysis, including fundamental algorithms for image segmentation and registration. VTK is an open-source, widely adopted, software system for 3D computer graphics, modeling, image processing, volume rendering, scientific visualization, and information visualization. The student will gain understanding of the working of all subroutines and practical application implementing these routines into customized workflow. The course will also introduce the use of OpenCV for applying computer vision and machine learning algorithms to biomedical images and data. Moreover, a full software development environment will be employed to create release-quality applications. This will include the use of source version control to track code changes and bugs, Qt for user interface development, CMake for development environment control, and Visual Studio C++ for the coding environment (Python is also permitted for students with substantial experience working with the language). This state of the art forms the basis for most medical visualization software used today, and students will learn the use of these tools and complete required exercises and projects, with an emphasis on real-world clinical applications.

Prerequisites

ENGS 65 or Permission of the Instructor