Curriculum
| Course Number | Summary | English |
|---|---|---|
| BME701 | Medical Physiology | |
| This course is an introduction to medical physiology for graduate students. It covers introductory cell biology, muscle, cardiovascular system, circulation, body fluids and kidney, Blood, respiration and digestive system. And then it also covers, in the second half of class, the structure and function of the human brain. | ||
| BME704 | Engineering Mathematics | |
| This class is designed to provide basic mathematical principles and methodologies that can be employed and applied to researches in the area of biomedical engineering and electronic/computer engineering. Emphasis is given to understanding of the fundamental principles in linear algebra, and the students are encouraged to study its applications. | ||
| BME709 | Digital Signal Processing | |
| This lecture is about the methodology of neuro-imaging research like experimental design, data acquisition and analysis, It covers anatomy co-registration, physiological noises, experimental design, image segmentation, surface analysis, and statistical analysis. | ||
| BME711 | Medical Image Processing | |
| - | ||
| BME712 | Pattern Recognition | |
| This class covers basic theories of pattern classification. Topics include distribution-free classification, statistical classification, supervised classification, unsupervised classification, neural nets, and machine learning. | ||
| BME717 | Medical Imaging System | |
| The conceptual, mathematical and statistical aspects of imaging science, and a survey from this formal viewpoint of various medical imaging modalities, including film screen radiography, positron and x-ray computed tomography, ultrasonic and magnetic resonance imaging | ||
| BME722 | Neural prosthetic technology | |
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This course covers the basic and advanced principles, concepts, and operations of neural prosthetic devices. The origin and nature of neural signals are also studied. Especially, electrical instrumentations which can replace the injured sensory or motor functions in humans will be reviewed. This will be followed by emerging frontiers of cellular and molecular medical technologies. |
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| BME724 | Biofludics | |
| This course introduces basic concepts of biological transport phenomena and helps the design of micro/nano fluidic devices for medical and biotechnological applications. This course also covers topics in fluid mechanics, mass transport, and biochemical interactions, with engineering concepts motivated by specific biological problems. All students are required to present one application topic in biological systems at the end of semester. | ||
| BME725 | Future medical technologies | |
| - | ||
| BME731 | Fuctional magnetic resonance imaging:Experiment and analysis | |
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This lecture is about the methodology of neuro-imaging research like experimental design, data acquisition and analysis, It covers anatomy co-registration, physiological noises, experimental design, image segmentation, surface analysis, and statistical analysis. |
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| BME741 | Magnetic Resonance Imaging | |
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This course covers the principles of magnetic resonance imaging(MRI) and its roles in clinical practices and medical research. The students will learn nuclear magnetic resonance(NMR) physics, MRI system components, imaging principles, MRI pulse sequences, and use of MRI in life science. The students will have opportunity to do MRI experiments with a 3.0 Tesla MRI system. |
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| BME751 | Bio Signal Processing | |
| This class covers basic theories of deterministic and probabilistic methods of signals and systems analysis. Topics include Fourier transform, Laplace transform, z-transform, random variables, random process, probability density functions, correlation functions, spectral analysis, and time-series analysis. | ||
| BME761 | Artificial Organs | |
| This course deals with principles of artificial organs that are currently used or will be used in the near future. In addition to studies components of artificial organs for the improvement of safety and convenience, the problems related with the applications of various artificial organs are studied. Topics include human kidney and artificial kidney devices, human lung and artificial heart-lung devices, human pancreas and artificial pancreatic devices, human heart block and artificial hearts. | ||
| BME771 | Neuroscience | |
| - | ||
| BME775 | Advanced Biofluid Mechanics | |
| This course covers the basic and advanced concepts of biofluidics, microfabrication, biochemical technologies and the principles of designing nanobio devices for biomedical applications. | ||
| BME779 | Bioelectricity | |
| Bioelectricity is the electrical phenomenon of life processes. The basic unit of this phenomenon is a cell which is polarized by certain energy-consuming processes. Specialized classes of cells that have electrically excitable membranes such as neurons or muscle cells have additional capabilities of developing action potentials. Many biomedical instruments such as electroencephalography, electrocardiography or electromyography measure the compounds of these action potentials from the brain, heart, and muscle, respectively. In this class, the basic biological mechanisms behind bioelectricity and their applications will be introduced. | ||
| BME780 | Applications in Deep Learning | |
| This course aims to cover various deep learning models based on the basic principles of deep learning. In this course, students will learn unsupervised learning such as adversarial generative networks (GANs), including existing supervised learning, and implement the code based on the theory. This course aims to broaden the understanding of deep learning applications using data such as various images and signals, and to cultivate experts who can lead a new paradigm of artificial intelligence. | ||
| BME781 | Medical Artificial Intelligence | |
| This course aims to learn the state-of-the-art papers, apply them to practice, and enhance the expertise in medical artificial intelligence. This course also covers the project for the state-of-the-art algorithms for medical artificial intelligence, which fosters experts in both theory and practice. | ||
| BME782 | Block chain Technology in Healthcare | |
| This course aims to cover distributed ledger technology, immutable records that cannot be changed or manipulated, and smart contract, which are the core elements of blockchain. It also covers the types of blockchains and networks. This course aims to broaden the understanding of the various use cases of blockchain technology and its application in the healthcare field. In particular, this course covers the establishment of a medical information distribution system using blockchain technology, the establishment of an integrated patient medical information system through blockchain, and the provision of customized medical information according to the characteristics of patients by utilizing the collected patients' big data and blockchain-based smart contract technology. | ||
| BME802 | Advanced MRI | |
| This course covers advanced topics in magnetic resonance imaging which includes high field MRI system components, parallel imaging techniques, and functional imaging techniques. Prerequisite includes NMR physics, basic MRI principles, and digital signal processing. The students will do team projects which aim at developing MRI pulse sequences and data processing techniques using the 3.0 tesla MRI system installed at the department. | ||
| BME810 | Biophotonics and biosensor technology | |
| This course contains a series of PBL type lectures on optics applications to biophotonics and biosensor systems. | ||
| BME815 | Independent study 1 | |
| This course is designed for the Ph.D. course students to do their own research works independently under supervision of their advisors. The Ph.D. students are encouraged to set the objectives of their research works and to do development of theories and methodologies to achieve the objectives. At the end of semester, the students must give the reports in a technical paper form to their advisors for grading. | ||
| BME816 | Independent study2 | |
| This course is designed for the Ph.D. course students to do their own research works independently under supervision of their advisors. The Ph.D. students are encouraged to set the objectives of their research works and to do development of theories and methodologies to achieve the objectives. At the end of semester, the students must give the reports in a technical paper form to their advisors for grading. | ||
| BME818 | Rehabilitation Engineering | |
| Design of devices for persons with physical, sensory or cognitive impairments, interdisciplinary study on specific disabilities | ||
| BME819 | Functional Magnetic Resonance Imaging | |
| In this course, we study the methodology of research using functional magnetic resonance images. Considering that this field is integrated use of magnetic resonance imaging, statistics and neuroscience, contents such as neural activity degree from the magnetic resonance image data, experiment design, preprocessing and analysis of data are handled. In addition, introduction of neurophysiology is also included in the lecture to enhance students' understanding of subjects. | ||
| BME821 | Principles of bioanalytical instrumentations | |
| The main objective of course is to study bio-instruments such as flow cytometer, electrophoresis, spectrometer and chomatography which are used to measure biological particles such as cells, DNA and protein. Upon the successful completion of the course, students will understand the bacis principles of the bio-instruments, know about their performance and operation, and finally a new concept of bio-instruments | ||
| BME822 | Microsystem Fabrication and Design | |
| This course will combine theory lectures and design/fabrication lectures to provide students with and introduction to microsystem implementation. The goals of this course are to provide backgrounds on : 1) microsystem introduction and applications, 2) device design and simulation tooles (ex. MEMS resonator design), 3) fabrication methods using silicon/non-silicon micromachining |