Mark Haidekker's Courses

CSEE 4620/6620: Biomedical Imaging

(formerly ENGG 4620, and course contents have not changed)

Summary:

Starting with Conrad Wilhelm Röntgens discovery of the X-rays, medical diagnosis was revolutionized by non-invasive imaging techniques. This course will present modern imaging modalities: X-ray, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound imaging. In the first part, the physical principles and instrumentation will be covered. The second part will provide examples of images, and cover the four fundamental steps of image processing: Image enhancement, segmentation, quantification, and visualization.

Class schedule: Every fall semester Tue/Thu 5:00 - 6:15 pm, 213 Driftmier, unless specified otherwise by the Academic Office

Click here for the detailed course web page

ENGR 4210: Linear Systems

Summary:

Linear Systems deals with systems and signals. A system is any assembly of components that performs a specific purpose. Key to analyzing and modeling such a system is that some variables (a position, velocity, voltage, pressure, to name a few examples) are measurable. Those measurable variables are the signals. Moreover, a system in the context of this course comes with some means to influence its variables (such as a force compressing a spring, or a current providing a motor's torque).

Linear systems are approximations of real systems. Within limits, many systems can be interpreted as linear, which means that they have several specific properties. When a system is considered linear, its mathematical description is highly simplified. In this course, we introduce linear systems and learn how do describe and model those systems through linear differential equations and in the frequency domain with the help of the Laplace and Fourier transforms.

This course was taught by me in 2012, 2013, and 2014. Click here for the detailed course web page

ELEE 4220: Feedback Control Systems

Summary:

Feedback control systems are fundamental to many engineering projects. Whether you simply want to keep a room at constant temperature, or whether you want to precisely position a robot's arm - the ability to understand and design feedback controls is a key skill. In this course, we will learn how do model processes and systems. We will describe these systems with differential equations and with the Laplace and z- transform. We will cover what control means. A major focus of this course lies on stability criteria, the steady-state- and the dynamic response of a controlled system. We will use computer simulations and hands-on projects to implement feedback control systems.

Class schedule: Every spring semester Tue/Thu 2:00 - 3:15 am, 213 Driftmier, unless specified otherwise by the Academic Office
Prerequisites: Differential Equations, Linear Systems

Click here for the detailed course web page

ELEE 4790: Applied Biomedical Instrumentation

Summary:

So you have had Circuits and Linear Systems. You have had Sensors & Transducers and Feedback Controls. Perhaps you also had Electronics I/II or Mechatronics. But... how do you actually build a device?

This will be the focus of this lab-based course on Instrumentation. This course is open to BSBE, BSCSE, BSEE, and MCHE, and your expertise will be combined to realize in practice a device with biomedical focus, for example, a blood pressure cuff, a ECG monitor, or a pulse oxymeter. Teams will be composed of students from the different disciplines, and each team can select their own project (approval required). The two-hour lecture covers practical aspects of electronic device development, and during the lab session, you receive assistence in building the prototype device.

Class schedule: Every spring semester TBD

Prerequisites differ by major.

Click here for the detailed course web page

ENGG/CSCI 8840: Advanced Image Analysis and Visualization

Summary:

Whereas the course CSEE 4620, Biomedical Imaging, covers the imaging modalities and some image processing fundamentals, Advanced Image Analysis and Visualization covers cutting-edge algorithms for the quantitative analysis of biomedical images. We will discuss advanced techniques for image enhancement and restoration, image segmentation, image quantification, and image visualization.

At the end of this course, you will have gained knowledge of modern image analysis tools. You will know how these algorithms work, and you will know their strengths and limitations. You will be able to design an image analysis chain to achieve a desired outcome, and you will gain the ability to create your own image analysis algorithms in computer code.

If you want to continue on your own after this course, you will notice that the software we are using is free for you to download and use legally. This means that you can immediately put the gained knowledge to work for you, whether for yourself or in your lab.

Class schedule Spring 2010:
Tuesday/Thursday 5:00 - 6:15
unless specified otherwise by the Academic Office
Prerequisites: CSEE 4620 (grade C or better) or instructor's consent

Click here for the detailed course web page