Boston University
Hidden
Worlds - Introduction to Subsurface Sensing and Imaging (ENG EK 131/132)
Prof. Michael Ruane - Undergraduate
Course
Engineers often face the problem of detecting and imaging
objects that are hidden underground or underwater, or embedded in the
human body. A number of probes are possible, including optical beams,
x-rays, ultrasonic waves, or electromagnetic waves. Sensors are used
to detect the transmitted, reflected, or scattered waves, and the data
are used to extract information about the hidden objects. Examples of
applications include detecting tumors under human tissue, locating mines
under ground, or imaging fish under water. Standard techniques include
optical microscopy, x-ray radiography, ultrasonic imaging, magnetic
resonance imaging (MRI), computer assisted tomography (CAT), etc. The
designers of these systems must understand the physical models that
describe the probing and sensing processes, before they can develop
the necessary algorithms or software for solving the puzzle -- computing
the image distribution and identifying the target.
In this course (13 meetings over 6 weeks), you will
learn the basic ideas behind probing hidden targets using various waves,
including the basic principles of the more prevalent imaging techniques.
You will develop the concept of modeling and learn about methods of
reconstruction from measured data. Simplified test projects will be
demonstrated in the 'High Tech Tools and Toys' Lab.
This is now a 2-credit stand-alone course. NU students
could choose to take a second module, or (possibly) enroll for only
2 credits.
Day(s) and Time(s): Tuesday/Thursday 3:00-5:00.
Distance Learning: NO - Available to BU and NU
Students Only.
Introduction
to Photonics (ENG EC 560)
Prof. Hatice Altug – Both Graduate
and Undergraduate Course
Introduction to ray optics, wave optics, Fourier optics
and holography, absorption, dispersion. Polarization, anisotropic media,
and crystal optics. Guided-wave and fiber optics. Elements of photon
optics. Laboratory experiments: interference; diffraction and spatial
filtering; polarizers, retarders, and liquid-crystal displays; fiber-optic
communication links. 4 cr.
Day(s) and Time(s): Monday/Wednesday 4:00pm
– 6:00pm.
Distance Learning: NO - Available to BU
and NU Students Only
Digital Image Processing and Communication (ENG
EC 520)
Prof. Janusz Konrad – Both Graduate
and Undergraduate Course
Review of signals and systems in multiple dimensions.
Sampling of still images. Quantization of image intensities. Human visual
system. Image color spaces. Image models and transformations. Image
enhancement and restoration. Image analysis. Image compression fundamentals.
Image compression standards (JPEG, JPEG-2000). Homework will include
MATLAB assignments. 4 cr.
Day(s) and Time(s): Monday/Wednesday 10:00am – 12:00pm.
Distance Learning: NO - Available to BU and NU Students Only
Northeastern
University
Modern
Imaging (ECE G293)
Prof. Edwin Marengo -
Graduate Level Courses
This course will cover basic and advanced topics in
imaging engineering. It will start with the formulation of typical forward
problems in electromagnetic and acoustic wavefield propagation and scattering,
with emphasis on biomedical and nondestructive testing applications,
and continue with a survey of imaging methodologies including the so-called
qualitative imaging methods.
Topics covered are: obstacle scattering, inhomogenous
medium scattering, uniqueness and stability in inverse scattering, imaging
with finite data, point-source method and its applications, singular
sources and shape reconstruction, linear sampling methods, signal-subspace-based
methods, noniterative approaches for the inverse medium problem, intensity-only
imaging, estimation theory in imaging and the question of super-resolution,
and selected topics in compressive sensing and quantum imaging
Prerequisites: ECE G202G Electromagnetic Theory
I.
Day(s) and Time(s): Monday/Thursday 11:45am – 1:25pm.
Distance Learning: NO - Available to BU and NU Students Only
Rensselaer
Polytechnic Institute
Cell
and Tissue Image Analysis
Prof. Badri Roysam - Graduate
Course
Survey of image analysis applications in biology, biotechnology,
and medicine; Introduction to biological microscopy and selected medical
imaging systems; Image reconstruction and preprocessing; Grayscale and
geometric corrections; adaptive image segmentation; blob analysis, cell/colony
counting, and cell morphometry; vessel and neuron tracing algorithms,
with applications to neurobiology and medicine; feature extraction,
pattern analysis, cluster analysis and classification; image registration
algorithms with applications to mosaicing, spatial referencing, motion
estimation, and change detection.
Prerequisites: A course in programming. Exposure
to basic statistical concepts is desirable.
This class is open to a variety of students ranging
from Biology majors to Engineering and Computing majors. Each student
will be required to perform some image analysis programming using MATLAB,
so some programming background is necessary. Individuals, or teams of
two students each, can do the course projects. Cross-disciplinary teaming
is encouraged, for example a biologist teaming with a computer scientist.
Expectations on these projects will vary based on the student's background.
Day(s) and Time(s): Lectures -To Be Determined
Distance Learning: YES - Available to BU, NU,
RPI, and UPRM StudentsAdditional Information: To view course information
from the Fall 2007 course (which will be similar in form and content
to the Fall 2008 course), go to http://www.ecse.rpi.edu/~roysam/CTIA/
where you will find files of voice-annotated PowerPoint lectures.
Boston University
Hidden
Worlds - Introduction to Subsurface Sensing and Imaging (ENG EK 131/132)
Prof. Michael Ruane - Undergraduate
Course
Engineers often face the problem of detecting and imaging objects that
are hidden underground or underwater, or embedded in the human body.
A number of probes are possible, including optical beams, x-rays, ultrasonic
waves, or electromagnetic waves. Sensors are used to detect the transmitted,
reflected, or scattered waves, and the data are used to extract information
about the hidden objects. Examples of applications include detecting
tumors under human tissue, locating mines under ground, or imaging fish
under water. Standard techniques include optical microscopy, x-ray radiography,
ultrasonic imaging, magnetic resonance imaging (MRI), computer assisted
tomography (CAT), etc. The designers of these systems must understand
the physical models that describe the probing and sensing processes,
before they can develop the necessary algorithms or software for solving
the puzzle -- computing the image distribution and identifying the target.
In this course (13 meetings over 6 weeks), you will learn the basic
ideas behind probing hidden targets using various waves, including the
basic principles of the more prevalent imaging techniques. You will
develop the concept of modeling and learn about methods of reconstruction
from measured data. Simplified test projects will be demonstrated in
the 'High Tech Tools and Toys' Lab.
Day(s) and Time(s): Tuesday/Thursday 3:30-5.
Distance Learning: NO - Available to BU and NU
Students Only
This is now a 2-credit stand-alone course. NU students could choose
to take a second module, or (possibly) enroll for only 2 credits.
Rensselaer
Polytechnic Institute
Cell
and Tissue Image Analysis
Prof. Badri Roysam - Graduate
Course
Survey of image analysis applications in biology, biotechnology,
and medicine; Introduction to biological microscopy and selected medical
imaging systems; Image reconstruction and preprocessing; Grayscale and
geometric corrections; adaptive image segmentation; blob analysis, cell/colony
counting, and cell morphometry; vessel and neuron tracing algorithms,
with applications to neurobiology and medicine; feature extraction,
pattern analysis, cluster analysis and classification; image registration
algorithms with applications to mosaicing, spatial referencing, motion
estimation, and change detection.
Prerequisites: A course in programming. Exposure
to basic statistical concepts is desirable.
This class is open to a variety of students ranging
from Biology majors to Engineering and Computing majors. Each student
will be required to perform some image analysis programming using MATLAB,
so some programming background is necessary. Individuals, or teams of
two students each, can do the course projects. Cross-disciplinary teaming
is encouraged, for example a biologist teaming with a computer scientist.
Expectations on these projects will vary based on the student's background.
Day(s) and Time(s): Lectures -To Be Determined
Distance Learning: YES - Available to BU, NU,
RPI, and UPRM Students
Additional Information: To view course information
for the Fall 2006 course which will be similar in form and content to
the Fall 2007 course, go to http://www.ecse.rpi.edu/~roysam/CTIA/ where you will find files of voice-annotated PowerPoint lectures.
Northeastern
University
Biological
Imaging (Bio U581 and Bio G281)
Prof. Donald O'Malley - Both
Undergraduate and Graduate Level Courses
This course will introduce students to state-of-the-art
imaging methodologies that are used in the biological and biomedical
sciences.
Advances in Imaging Techniques, together with new Optical Probes,
have fostered a revolution in Biological Imaging. Such techniques
are now at the frontiers of every area of biology, especially cell,
molecular and developmental biology, as well as neuroscience. The
3-fold goals of this course are to:
(1) Introduce students to the optical physics & the imaging devices used in microscopy,
(2) Survey cutting-edge imaging applications in cellular and neural biology and
(3) Critique the application of these techniques within the biomedical research
literature.
Prerequisites: Genetics. This course is intended
for Junior/Senior students in Biology and related disciplines, as
well as graduate students. Students with a science background, but
lacking genetics, should consult the instructor. Graduate students
will be graded separately from undergraduate students. Having taken
Biochemistry is a plus, but is certainly not necessary; non-biologists
have historically fared well in this course.
Notes: For more information, see the
Spring 2007 Flyer.