Biophotonics Imaging Laboratory

Academics

Academics

UIUC Courses

Optics, Physics, & Imaging:

  • ECE/BIOE 380 - Biomedical Imaging (Fall)
    Studies the fundamentals and applications of six medical imaging techniques: X-ray imaging, computed tomography, nuclear medicine, magnetic resonance imaging, ultrasound, and optical imaging. In addition, introductory material on general image formation concepts and characteristics is presented.

  • ECE 450 - Fiber Optic Communications (Spring)
    Characterization, design, and lab measurements of optical fibers and lightwave channels, optical transmitters, receivers, and amplifiers; quantum and thermal noise processes; design of optical receivers; multimode and single-mode link analysis.

  • ECE 455 - Optical Electronics (Fall)
    Topics including optical beams and cavities, semiclassical theory of gain, characteristics of typical lasers (gas, solid state, and semiconductor), and application of optical devices are discussed.

  • ECE/BIOE 460 - Optical Imaging (Spring)
    Introduction to visible and infrared imaging systems covering fields, optical elements, electronic sensors, and embedded processing systems. Lectures and labs cover active and passive illumination, ranging, holography, polarization, coherence, spectroscopy and sampling with an emphasis on electronic optomechanical control and data acquisition.

  • ECE/BIOE 467 - Biophotonics (Spring)
    Different imaging modalities, such as OCT, CARS, FRET, SHG/THG, confocal microscopy, MPM, nonlinear optics, as well as their clinical applications are introduced. In each lecture, students lead a brief discussion about a related journal article to provide additional information, which is not yet covered in the textbook. 

  • ECE 468 - Optical Remote Sensing (Not currently offered)
    Optical sensors including single element and area arrays (CCDs), and systems including imager, spectrometer, interferometer and lidar optical principles and light gathering power are discussed.

  • ECE 495 - Photonic Device Laboratory (Spring)
    Introduction to active photonic devices and lightwave technology. Hands-on experience with several classes of lasers (HeNe laser, semiconductor edge emitting lasers, vertical cavity surface emitting lasers), photodetectors, and photonic systems. Familiarization with experimental optical characterization techniques and equipment.

  • ECE 520 - Electromagnetic Waves and Radiating Systems (Fall) 
    Fundamental electromagnetic theory with applications to transmission lines, waveguides, and antennas is covered. Introduction to the solution of advanced problems in static electric and magnetic fields is presented.

  • ECE 529 - Light-Matter Interactions (Fall)

    Light-matter interaction is explored using a primarily classical approach. This course examines optical properties, including refraction, dispersion, and absorption, in gases, liquids, and solids, emphasizing metals and dielectrics. Topics include dispersion relations, optical activity, Faraday rotation, and the influence of quantum mechanics on optical properties. Nonlinear contributions to polarization, which result in new frequencies and irradiance-dependent properties, are discussed. The course also addresses light's interactions with artificial photonic materials, specifically metamaterials and metasurfaces. 

  • ECE 536 - Integrated Optics and Optoelectronics (Not currently offered)
    Integrated optical and optoelectronic devices and the theory of optical devices including laser sources, waveguides, photodetectors, and modulations of these devices are discussed.

  • ECE 564 - Modern Light Microscopy (Not currently offered)
    Current topics in modern light microscopy including principles (statistical optics, Gaussian optics, elastic light scattering, dynamic light scattering), traditional microscopy (bright field, dark field, DIC, phase contract, confocal, epi-fluorescence, confocal fluorescence), and advanced techniques (multiphoton, CARS, STED, FRET, FIONA, STORM, PALM, quantitative phase) are discussed.

  • ECE 569 - Inverse Problems in Optics (Not currently offered)
    Covers physical optics, solution of linear inverse problems, and computed imaging for forward problems in diffraction, asymptotics, ray propagation, x-ray projections, scattering, sources, optical coherence tomography, and near-field optics. Solution of associated inverse problems including back-propagation, back-projection, Radon transforms (x-ray CT), inverse scattering, source localization, interferometric synthetic aperture microscopy, and near-field tomography are discussed.

  • ECE 570 - Nonlinear Optics (Fall)
    Light propagation in anisotropic crystals, second- and third-order nonlinear susceptibility and electro-optic effect, and discussion of the relationship of these effects along with such applications as light modulation, harmonic generation, and optical parametric amplification and oscillation is covered.

  • ECE 498/ECE 598 - Special Topics in ECE

    • ECE 498 GP: Fourier Optics (Not currently offered)

    • ECE 498 LG: Optical Design of Imaging Systems (Not currently offered)

  • PHYS 402 - Light (Fall, Spring)
    Covers general theory on wave kinematics, geometrical optics (basic concepts, ray-tracing and matrix formalism, Gaussian imaging by thick lenses, stops, and apertures, and intensity relations), interference, coherence, diffraction, polarization, Fresnel-Kirchhoff formulation, Fraunhofer case, Fresnel case, and holography. 

  • PHYS 542 - Quantum Mechanics and Spectroscopy (Not currently offered)
    Time-dependent problems are introduced, followed by and expanded on for various chemical systems. Light-matter interactions and the corresponding spectroscopies are emphasized. Single and multi-photon processes are discussed, as are the principles of electron spectroscopy, vibrational spectroscopy, NMR, coherent interactions, etc.

  • CHEM 540 - Introductory Quantum Mechanics at the Graduate Level (Not currently offered)
    Introductory to the postulates and formalisms of quantum mechanics applied to chemical systems. Introduces foundational mathematics, postulates and formalisms used in the study of quantum systems. Solutions to the time-independent Schrodinger equation are then used to model quantum mechanical systems, including the harmonic oscillator, potential barriers, tunneling, etc. Angular momentum and spin introduced. Course begins with simple atomic models, and increases in complexity. Numerical and computational approaches to complex systems such as perturbation theory and the Born-Oppenheimer approximation introduced. Time-dependent problems are introduced at the conclusion of the course.

Signal/Image Processing:

  • ECE 310 - Digital Signal Processing (Fall, Spring)
    Introduces a DSP concept, such as convolution, Linear time invariant (LTI) system, sampling theory, Fourier transform, Z-transform, Design of FIR and IIR filter.

  • ECE 418 - Image & Video Processing (Spring)
    Concepts and applications in image and video processing; introduction to multidimensional signal processing: sampling, Fourier transform, filtering, interpolation, and decimation; human visual perception; scanning and display of images and video; image enhancement, restoration and segmentation; digital image and video compression; image analysis. Laboratory exercises promote experience with topics and development of C and MATLAB programs. 

  • ECE 420 -  Embedded DSP Laboratory (Fall, Spring)
    Develops real-time digital signal processing (DSP) systems using a DSP microprocessor. Several structured laboratory exercises, such as sampling and digital filtering, followed by an extensive DSP project.

  • ECE 513 - Vector Space Signal Processing (Spring)
    Rigorous presentation of key mathematical tools in a vector space framework, and their applications in signal processing, including: finite and infinite dimensional vector spaces, Hilbert spaces, linear operators, inverse problems (e.g. deconvolution, tomography, Fourier imaging), least-squares methods, conditioning and regularization, matrix decompositions, subspace methods, bases and frames for signal representation (e.g. generalized Fourier series, wavelets, splines), Hilbert space of random variables, random processes, signal and spectral estimation are discussed.

  • ECE 544 NA - Pattern Recognition (Fall)
    Lectures and discussions related to advanced topics and new areas of interest in signal processing: speech, image, and multidimensional processing are presented. 

  • ECE 547 - Topics in Image Processing (Not currently available) 
    Examines fundamental concepts, techniques, and directions of research in image processing. Topics include two-dimensional Fourier transform and filtering, image digitization, coding, restoration, reconstruction, analysis, and recognition.

  • ECE 551 - Digital Signal Processing II (Fall)
    Covers basic concept review of digital signals and systems; computer-aided digital filter design, quantization effects, decimation and interpolation, and fast algorithms for convolution and the DFT; introduction to adaptive signal processing.

  • ECE 558 - Digital Imaging (Spring)
    Covers multidimensional signals, convolution, transforms, sampling, and interpolation; design of two-dimensional digital filters; sensor array processing and range-doppler imaging; applications to synthetic aperture radar, optics, tomography, radio astronomy, and beam-forming sonar; image estimation from partial data.

Cellular and Biology/Medicine:

  • MCB 250 - Molecular Genetics (Fall, Spring)
    A lecture/discussion course that provides detailed coverage of genetic variation, gene organization, gene expression, and gene regulation in a variety of organisms. 

  • MCB 252 - Cells, Tissues, and Development (Fall, Spring)
    Functional organization and physiology of cells and tissues, including cellular signaling, cellular interactions, and developmental processes. 

  • MCB 402 - Systems and Integrative Physiology (Spring)
    Examines human systems physiology. Topics to be covered include the nervous and endocrine systems, muscle physiology, cardiac physiology, respiratory physiology, blood and immune homeostasis, renal physiology, and gastrointestinal physiology and energy homeostasis. Special emphasis is on homeostatic control and integration of body systems in both health and disease. 

  • MCB 450 - Introduction to Biochemistry (Fall, Spring)
    It is an introduction to biochemistry, a discipline devoted to understand living systems in terms of chemical principles.

  • MCB 465 - Human Metabolic Disease (Spring)
    Examination of the molecular and physiological basis of human metabolic disease. Disruption of metabolic and energy homeostasis plays key roles leading to metabolic disorders. Examines how lipid/glucose levels and energy balance are controlled in health and how they are abnormally regulated in disease states. Covers current topics related to control of metabolism including aging and circadian rhythms. Methodologies leading to scientific discoveries and potential preventive and therapeutic agents are discussed.

  • BIOE 476 - Tissue Engineering (Fall)
    Principles of the tissue environment and its application to engineering biological systems are discussed. Emphasis on stem-cell lineages, cell-cell and cell-ECM communication and transduction mechanisms. Discusses molecular signaling, cell migration, and the corresponding cellular and ECM components needed to perform these tasks. Tools used for characterizing and developing engineered tissue are introduced, as are models for testing engineered tissues with in vitro and in vivo models.

Machine Learning:

  • ECE 448/CS 440 - Introduction to Artificial Intelligence (Fall, Spring)
    Introductory description of the major subjects and directions of research in artificial intelligence; topics include AI languages (LISP and PROLOG), basic problem solving techniques, knowledge representation and computer inference, machine learning, natural language understanding, computer vision, robotics, and societal impacts.

  • ECE 449/CS 446 - Machine Learning (Fall, Spring)
    Covers discriminative models, generative models, and reinforcement learning models. In particular, various ML techniques, such as linear regression, logistic regression, support vector machines, deep nets, structured methods, learning theory, kMeans, Gaussian mixtures, expectation maximization, VAEs, GANs, Markov decision processes, Q-learning and Reinforce, are discussed.

  • ECE 494/CS 444 - Deep Learning for Computer Vision (Fall, Spring)
    Provides an elementary hands-on introduction to neural networks and deep learning with an emphasis on computer vision applications. Topics include: linear classifiers; multi-layer neural networks; back-propagation and stochastic gradient descent; convolutional neural networks and their applications to object detection and dense image labeling; recurrent neural networks and state-of-the-art sequence models like transformers; generative adversarial networks and variational autoencoders for image generation; and deep reinforcement learning.

  • ECE 549/CS 543 - Computer Vision (Fall)
    Information processing approaches to computer vision, algorithms, and architectures for artificial intelligence and robotics systems capable of vision: inference of three-dimensional properties of a scene from its images, such as distance, orientation, motion, size and shape, acquisition, and representation of spatial information for navigation and manipulation in robotics. 

Other Interesting Courses:

  • ECE/BIOE 414 - Biomedical Instrumentation (Fall, Spring)
    Introduction to engineering aspects of the detection, acquisition, processing, and display of information and signals from living systems. Topics discussed include biomedical transducers and systems for measurement of biopotentials, force, pressures, blood flow, and heart sounds, as well as instrumentation for cell type and surface marker identification.

  • ECE/BIOE 415 - Biomedical Instrumentation Lab (Fall, Spring)
    Studies medical instrumentation and transducers for static and dynamic inputs and measures actual biomedical signals.

  • ECE 437 - Sensors and Instrumentation (Fall)

    Hands-on exposure to fundamental technology and practical application of sensors. Capacitive, inductive, optical, electromagnetic, and other sensing methods are examined. Instrumentation techniques incorporating computer control, sampling, and data collection and analysis are reviewed in the context of real-world scenarios.

  • BIOE 571 - Biological Measurement I (Fall)
    Introduces fundamental concepts related to the detection and analysis of biological analytes, biomedical images, and physiological parameters.  Topics include signal-to-noise analysis, noise characterization, data aliasing, analog-to-digital conversion, and common strategies for noise reduction.  The fundamental phenomena behind biological measurements such as DNA sequencing, fluorescence microscopy. MRI imaging, OCT imaging, and ultrasound imaging are discussed along with the factors that influence noise and contrast from the standpoint of fundamental physics, instrumentation hardware, and post-measurement data/signal processing.  

  • PHYS 498 ART - Where Art Meets Physics (Not currently available)
    Experiences the exciting ways in which science has joined hands with a broad spectrum of the arts, inclusive of the visual arts, theater, music, literature, and more, and to the marvelous creations that have emerged from this synergy. Going beyond analyzing this synergy, students will become creators themselves by using the knowledge gained in the course, forming teams, and learning from one another.

  • PHYS 595 - Communicating Scientific Research (Spring)
    Helps graduate students in science and engineering improve their scientific writing and presentation skills through instruction and detailed feedback on a variety of technical writing and presentation styles common in science and engineering practice. These assignments include a journal-style research paper, an NSF-style proposal, an editor cover letter, a referee report, and journal club and research presentations.

  • MCB 540 - Scientific Writing (Fall)
    Study of scientific communication, geared toward biologists. Topics include writing mechanics, grammar and sentence structure, abstracts for different audiences and purposes, grant writing, manuscript preparation, figure construction, oral presentations, and the grant-review process.

  • MCB/NEUR/PSYC 542/543 - Interdisciplinary Approaches to Neuroscience I (Fall) & II (Spring)
    Introduction for graduate students to the breadth and interdisciplinary nature of Neuroscience, and to the topic areas investigated broadly by faculty of the Neuroscience Program (NSP). The course emphasizes concepts and methods rather than facts, and includes discussions and career development lectures. Team taught by multiple NSP faculty, senior students and postdocs, the course covers topics in cellular, molecular, computational, behavioral and clinical neuroscience as well as neuroengineering.