Biomedical Engineering combines engineering, physics, and life sciences to develop technologies for healthcare. This course provides an integrated overview of key areas including instrumentation, medical imaging, signal and image processing, biomedical informatics, prosthetics, and neural engineering, with a strong emphasis on clinical applications and emerging technologies.
Lecture: Course materials and notes will be available on the KHU Klass portal
Lecture – 1 (Introduction to Biomedical Engineering) Scope of biomedical engineering, interdisciplinary nature, clinical translation, overview of major domains.
Lecture – 2 (Human Physiology for Engineers) Cellular physiology, organ systems, bioelectric phenomena, homeostasis.
Lecture – 3 (Biomedical Signals and Systems) Types of physiological signals (ECG, EEG, EMG), signal characteristics, noise and artifacts.
Lecture – 4 (Biomaterials and Tissue Interaction) Material properties, biocompatibility, implants, degradation, host response.
Lecture – 5 (Biomedical Instrumentation I – Sensors) Electrodes, transducers, biosensors, signal acquisition fundamentals.
Lecture – 6 (Biomedical Instrumentation II – Systems Design) Amplifiers, filtering, analog-to-digital conversion, safety standards.
Lecture – 7 (Medical Imaging Overview) X-ray, CT, MRI, Ultrasound, PET, Optical imaging, comparative principles.
Lecture – 8 (X-Ray and CT Imaging) Physics, detectors, reconstruction basics, radiation dose considerations.
Lecture – 9 (MRI Fundamentals) Spin physics, relaxation, contrast mechanisms, pulse sequence basics.
Lecture – 10 (Advanced MRI and Quantitative Imaging) Diffusion, functional MRI, spectroscopy, quantitative biomarkers.
Lecture – 11 (Ultrasound and Optical Imaging) Acoustic imaging, Doppler, optical modalities, clinical applications.
Lecture – 12 (Signal Processing in Biomedical Engineering) Filtering, Fourier analysis, time-frequency methods.
Lecture – 13 (Medical Image Processing) Segmentation, registration, feature extraction, quantitative analysis.
Lecture – 14 (Biomedical Informatics) Electronic health records, data standards, interoperability, clinical workflows.
Lecture – 15 (Machine Learning in Healthcare) Supervised learning, classification, regression, model evaluation.
Lecture – 16 (Deep Learning for Medical Imaging) CNNs, reconstruction, segmentation, AI-driven diagnostics.
Lecture – 17 (Biomechanics and Movement Analysis) Kinematics, kinetics, musculoskeletal modeling.
Lecture – 18 (Biomedical Prosthetics) Limb prostheses, materials, control strategies, patient adaptation.
Lecture – 19 (Rehabilitation Engineering) Assistive devices, robotics in rehabilitation, human-machine interfaces.
Lecture – 20 (Neural Engineering and Interfaces) Brain-machine interfaces, neural signal acquisition, decoding strategies.
Lecture – 21 (Neural Prosthetics) Cochlear implants, deep brain stimulation, motor prosthetics.
Lecture – 22 (Wearable and Digital Health Technologies) Sensors, remote monitoring, mobile health, personalized medicine.
Lecture – 23 (Regulatory, Ethics, and Clinical Translation) FDA/CE processes, safety, ethics, data privacy.
Lecture – 24 (Case Studies and Future Directions)
Lecture – 1 (Introduction to Medical Imaging Systems) – Overview of imaging modalities, clinical role, and system-level perspective.
Lecture – 2 (Human Anatomy for Imaging) – Relevant anatomy and contrast mechanisms across modalities.
Lecture – 3 (Radiation Physics I) – Interaction of radiation with matter, attenuation and scattering.
Lecture – 4 (Radiation Physics II) – Radiation dose, units, biological effects and safety.
Lecture – 5 (X-Ray Imaging – Physics) – X-ray generation, spectra and system design.
Lecture – 6 (X-Ray Imaging – Detectors and Applications) – Detectors, image formation and clinical applications.
Lecture – 7 (CT – Physics I) – CT geometry, projections and acquisition principles.
Lecture – 8 (CT – Physics II) – Helical CT and multi-slice systems.
Lecture – 9 (CT – Reconstruction) – Filtered backprojection and iterative reconstruction.
Lecture – 10 (CT Dose and Clinical Applications) – Dose optimization, artifacts and clinical use.
Lecture – 11 (MR – Physics I) – Spin physics and magnetization fundamentals.
Lecture – 12 (MR – Physics II) – Relaxation mechanisms and contrast formation.
Lecture – 13 (MR – Physics III) – Spatial encoding and k-space concepts.
Lecture – 14 (MR – Pulse Sequences) – Spin echo, gradient echo and fast imaging.
Lecture – 15 (MR Advanced and Clinical Applications) – Diffusion, fMRI and quantitative MRI.
Lecture – 16 (MR Safety and Bio-effects) – SAR, RF exposure and safety considerations.
Lecture – 17 (Ultrasound – Physics) – Acoustic propagation, transducers and imaging principles.
Lecture – 18 (Ultrasound – Clinical Applications) – Doppler imaging and clinical applications.
Lecture – 19 (PET – Physics) – Positron emission, detectors and coincidence imaging.
Lecture – 20 (PET – Clinical Applications) – Oncology, neurology and hybrid imaging systems.
Lecture – 21 (Optical Imaging) – Fluorescence, bioluminescence and optical tomography.
Lecture – 22 (Image Processing and AI in Imaging) – Segmentation, reconstruction and deep learning.
Lecture – 23 (Artifacts and Quality Assurance) – Image artifacts, correction techniques and QA protocols.
Lecture – 24 (Clinical Workflow and Future Directions) – PACS systems, data handling and emerging trends in imaging.