Students will be able to apply the principles of electronic circuits and devices to the use and design of instrumentation in the biomedical area. They will have gained a basic knowledge of the operating principles of electrical and other transducers, analog and digital instrumentation, applied signal acquisition and processing, electrical safety in the medical environment, electrical properties of nerve and muscle physiology; and instrumentation used in cardiopulmonary, neurological, surgical, and rehabilitation areas of medicine.
Lecture 1 – Introduction
Lecture 2 – Sensor Models
This is a preview of Lecture Notes on Biomedical Instrumentation and Design. Read the full post (287 words, 2 images, estimated 1:09 mins reading time)
This course has two components. On the one hand, it is an introduction to digital image analysis presenting selected fundamental problems in medical image analysis, computer vision, photo/video editing, and graphics. We cover such basic concepts as image segmentation, registration, object recognition/matching, tracking, texture, etc. On the other hand, this is an applied course on standard computer science algorithms where students develop practical understanding of dynamic programming, graph based algorithms, computational geometry methods, etc. In fact, image analysis provides a stimulating environment for studying algorithms as their outputs can be intuitively visualized. Students with previous background in algorithms will be exposed to applications in image analysis, while students already familiar with problems in imaging will learn efficient methods based on standard CS algorithms. The course emphasizes the design, analysis, and implementation of algorithms in the context of 2D/3D medical images, photo and video data.
This is a preview of Lecture notes : Algortihms used for Medical Image Processing. Read the full post (324 words, 1 image, estimated 1:18 mins reading time)