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). Moreover, a full software development environment will be employed to create release-quality applications. The course will also introduce the use of OpenCV for applying computer vision and machine learning algorithms to biomedical images and data. The student will gain understanding of the working of all subroutines and practical application implementing these routines into customized workflow. ![]() VTK is an open-source, widely adopted, software system for 3D computer graphics, modeling, image processing, volume rendering, scientific visualization, and information visualization. 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. ![]() 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. 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. Application examples are drawn from aerospace, biomedical, civil, computer, electrical, industrial, mechanical, and systems engineering. Equilibrium modeling concepts for strategic form games and extensive form games are introduced as extensions of the core optimization concepts. Uncertainty associated with real-world modeling is captured through simulation techniques with specific emphasis on discrete events simulation. Key results and applications of queuing models are presented. Various network models and the corresponding solution algorithms are discussed. After a brief overview of linear and discrete optimization models, the course covers four main types of techniques: network models, queuing theory, discrete events simulation and game theoretic analysis. Emphasis is on developing strong formulations, understanding key solution concepts, developing efficient algorithms, and grasping the advantages and limitations of each approach. This course provides an overview of a broad range of deterministic and probabilistic operations research models with a focus on engineering applications. Students will be expected to have access to an entry-level digital camera, either standalone or attached to a cell phone or tablet computer. Students will participate in a course-long group project that demonstrates their understanding of and ability to harness these new technologies. Students will explore and learn the basic science and technology through a combination of in-class lectures and active hands-on experimentation with digital cameras, image processing software and digital video systems. Specific attention will be paid to the scientific principles and engineering challenges underlying optics, computer processing chips, image processing software and algorithms, data compression and communication, and digital sensors as well as the basic principles of human vision and cognition. This course will introduce students to the fundamental concepts underlying a diverse and representative collection of modern digital imaging systems including cell phone cameras, medical imaging systems, space telescopes, computer games and animated movies. Such systems are affecting everyone today - from eyewitness documentation of social and political events to health care to entertainment to scientific discovery. ![]() Recent advances in electrical and computer engineering, computer science and applied mathematics have made remarkable digital imaging systems possible.
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