ECSE-6963 / BMED 6965
Cell & Tissue Image Analysis
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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.
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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.
Images from modern biological microscopes are
multi-dimensional, 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 aimed at a multi-disciplinary audience. 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
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Image analysis and quantitation needs arising in hypothesis testing, systems
biology, assays, structure and function studies, drug discovery, toxicology,
and tissue engineering
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Mini tour of modern
cell biology and histology
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Issues in Cell and
Tissue Image Analysis
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Examples from
contemporary applications throughout the course.
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Review of modern
biological imaging systems
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Basics of optical
microscopy instrumentation
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Low-level algorithms (deconvolution, unmixing)
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Molecular imaging using
fluorescence and related methods such as FLIM, FRET
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Fluorescent labeling
methods (immunofluorescence, fluorescent proteins);
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High-throughput and
time-lapse microscopy;
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Core Image Analysis
Methods
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Limitations of manual
and stereological assessment
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Common morphologies of
compartments, surfaces and signals;
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Segmentation
algorithms for core image objects;
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Algorithms for
tracking moving objects and change analysis;
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Object classification
and clustering algorithms;
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Intrinsic Measurements
(Feature extraction);
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Primary Associative
Measurements of spatial, temporal, and functional relationships;
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Protocols for
classical and edit-based validation, and performance assessment
– Secondary Associative Measurements and Cell networks
Grading
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Assignments (roughly
one per week) – 60%
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Term Project –
40%
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Generous reward for
effort
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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.