ECSE-6963, BMED 6961
Cell & Tissue Image Analysis
|
|
|
What
is this course about?
Image analysis is the business of making quantitative
measurements from images. In this course, we focus on multi-dimensional images
of biological cells, tissues, and organisms captured by modern optical
microscopes.
|
|
|
Modern microscope imaging systems are amazing (and expensive!).
They can capture 3-D structure and location of cells and tissue. By
fluorescence multiplexing, we can image multiple structures and functional
markers in their relative context. Using time-lapse imaging combined with a set
of techniques for live-cell imaging, we can record changes over time. These
changes could represent things like structural dynamics, cell movements, and
transport of molecules within a cell. Combining the above methods allows us to
record biological processes in their spatial & temporal context.
The images from modern biological microscopes are
multi-dimensional in nature, capturing the dimensions of space, optical
properties of tissue, spectra representing chemical information, and the
dimension of time.
This course is about systematic ways to make quantitative
measurements from these images. Basically, we are interested in two kinds of
measurements: intrinsic, and associative. Intrinsic measurements quantify
aspects of objects in each imaging channel. Associative measurements describe
the relationships among these objects in space and time. These measurements can
be combined with other forms of bio-informatics data to understand cells and
tissue.
Intended
Audience
This course is inter-disciplinary. Students in Biology, Biomedical
Engineering (BME), Electrical Computer & Systems Engineering (ECSE), and
Computer Science can all expect to benefit. You must have some prior
programming experience (MATLAB would be perfect). If you are an ECSE or CS
major, you must be willing to learn some basic biology. If you are a Biology or
BME major, you must be willing to pick up MATLAB programming skills.
Course
Topics
•
Image analysis and quantitation needs arising in hypothesis
testing, systems biology, assays, structure and function studies, drug
discovery, toxicology, and tissue engineering
– Mini tour of modern
cell biology and histology
– Issues in Cell and
Tissue Image Analysis
– Examples from
contemporary applications throughout the course.
•
Review of modern light microscopy systems (widefield,
fluorescence, confocal, multi-photon, multi-spectral, second-harmonic
generation, phase contrast, differential interference contrast, etc.)
– Imaging dimensions
(space, time, spectral channels, modalities);
– Role of imaging in
modern bioscience;
– High-throughput and
time-lapse microscopy;
– Spectral unmixing
methods;
•
Core Image Analysis Strategies
– Common morphologies
of compartments, surfaces and signals;
– Segmentation
algorithms for core image objects;
– Intrinsic
Measurements (Feature extraction);
– Classification and
pattern analysis;
– Associative
Measurements from Spatial, temporal, and functional associations;
Grading
•
Assignments (roughly
one per week) – 60%
•
Term Project – 40%
•
Generous reward for
effort
•
Off-campus students
will receive grade for local independent study course
Term Projects
The lectures are designed to give you a broad
understanding of the subject. The term project is designed to give you an
in-depth understanding of a selected topic. The ideal term project is a
cross-disciplinary one. It is conducted by a team of two students – one student
is from Biology or BME, and the other is from ECSE or CS. Each student
contributes equally.
At
the end of the semester, each term project will be presented in the form of a
poster presentation. The location and time of the presentation will be
announced in class. It is usually held during Finals Week. Off-campus students
will receive specific instructions during the weekly teleconferences.