Imaging Science MS

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Imaging Science: Online
Master of science degree

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Online Admissions Contact

Karen Palmer, Associate Director Combined Accelerated Programs
585-475-5656,

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A degree driven by real-time employer demand

These jobs are growing by 16%, more than twice the rate of overall labor market growth.

Imaging science job outlook

100%

Graduate outcomes rate

24

You may complete this degree in as few as 24 months

83K+

Average salary for imaging scientist

100%

Graduate knowledge rate

Program Highlights

The MS degree in Imaging Science curriculum emphasizes a systems approach to the study of imaging science. WIth a background in science or engineering, this degree will prepare you for positions in research, product development, and management in the imaging industry. The curriculum was developed in collaboration with industry partners to emphasize skills needed by their scientists, engineers, and managers. You may concentrate on one of several "system tracks," or customize your own track. You may choose to complete either a research thesis or a project and a paper in the non-thesis option. You may also perform your thesis research at your place of employment. The program can be completed on a full or part-time basis.

Curriculum packed with high-demand skills

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Research

Graduates apply their knowledge to research in areas of astronomy and space science, cultural artifact and document imaging, nanoimaging and materials, optics, remote sensing, and vision.

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Careers

Graduates work in various research and applied roles like Imaging Scientist, Imaging Systems Scientist, Imaging Systems Engineer, and Systems Engineer.

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Systems

Employers appreciate the ability of our graduates to apply the imaging chain towards a full systems perspective.

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Biomedical

Graduates are well prepared to contribute to both research and applied work in biomedical systems.

Curriculum

Thesis Option

IMGS-616
Fourier Methods for Imaging
Credits 3
This course develops the mathematical methods required to describe continuous and discrete linear systems, with special emphasis on tasks required in the analysis or synthesis of imaging systems. The classification of systems as linear/nonlinear and shift variant/invariant, development and use of the convolution integral, Fourier methods as applied to the analysis of linear systems. The physical meaning and interpretation of transform methods are emphasized.
IMGS-606
Graduate Seminar I
Credits 1
This course is focused on familiarizing students with research activities in the Carlson Center, research practices in the university, research environment and policies and procedures impacting graduate students. The course is coupled with the research seminar sponsored by the Center for Imaging Science (usually weekly presentations). Students are expected to attend and participate in the seminar as part of the course. The course also addresses issues and practices associated with technical presentation and technical writing. Credits earned in this course apply to research requirements.
IMGS-607
Graduate Seminar II
Credits 1
This course is a continuation of the topics addressed in the preceding course Imaging Science Graduate Seminar I. The course is coupled with the research seminar sponsored by the Center for Imaging Science (usually weekly presentations). Students are expected to attend and participate in the seminar as part of the course. The course addresses issues and practices associated with technical presentations. Credits earned in this course apply to research requirements.
IMGS-682
Image Processing and Computer Vision
Credits 3
This course will cover a wide range of current topics in modern image processing and computer vision. Topics will include introductory concepts in supervised and unsupervised machine learning, linear and nonlinear filtering, image enhancement, supervised and unsupervised image segmentation, object classification, object detection, feature matching, image registration, and the geometry of cameras. Assignments will involve advanced computational implementations of selected topics from the current literature in a high-level language such as Python, MATLAB, or Julia and will be summarized by the students in written technical papers. The course requires computer programming, linear algebra, and calculus.
IMGS-633
Optics for Imaging
Credits 3
This course provides the requisite knowledge in optics needed by a student in the graduate program in Imaging Science. The topics covered include the ray and wave models of light, diffraction, imaging system resolution.
 
Electives
Credits 3
 
Specialty Track Courses
Credits 6

Choose one of the following:

IMGS-619
Radiometry
Credits 3
This course is focused on the fundamentals of radiation propagation as it relates to making quantitative measurements with imaging systems. The course includes an introduction to common radiometric terms and derivation of governing equations with an emphasis on radiation propagation in both non-intervening and turbid media. The course also includes an introduction to detector figures of merit and noise concepts.
IMGS-620
The Human Visual System
Credits 3
This course describes the underlying structure of the human visual system, the performance of those structures and the system as a whole, and introduces psychophysical techniques used to measure them. The visual system's optical and neural systems responsible for collecting and detecting spatial, temporal, and spectral signals from the environment are described. The sources and extent of limitations in the subsystems are described and discussed in terms of the enabling limitations that allow practical imaging systems.
IMGS-790
Research & Thesis
Credits 1 - 6
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
 
Electives
Credits 3

Project Option

IMGS-616
Fourier Methods for Imaging
Credits 3
This course develops the mathematical methods required to describe continuous and discrete linear systems, with special emphasis on tasks required in the analysis or synthesis of imaging systems. The classification of systems as linear/nonlinear and shift variant/invariant, development and use of the convolution integral, Fourier methods as applied to the analysis of linear systems. The physical meaning and interpretation of transform methods are emphasized.
IMGS-682
Image Processing and Computer Vision
Credits 3
This course will cover a wide range of current topics in modern image processing and computer vision. Topics will include introductory concepts in supervised and unsupervised machine learning, linear and nonlinear filtering, image enhancement, supervised and unsupervised image segmentation, object classification, object detection, feature matching, image registration, and the geometry of cameras. Assignments will involve advanced computational implementations of selected topics from the current literature in a high-level language such as Python, MATLAB, or Julia and will be summarized by the students in written technical papers. The course requires computer programming, linear algebra, and calculus.
IMGS-633
Optics for Imaging
Credits 3
This course provides the requisite knowledge in optics needed by a student in the graduate program in Imaging Science. The topics covered include the ray and wave models of light, diffraction, imaging system resolution.
IMGS-740
Imaging Science MS Systems Project Paper
Credits 3
The analysis and solution of imaging science systems problems for students enrolled in the MS Project capstone paper option.
 
Electives
Credits 9
 
Specialty Track Courses
Credits 6

Choose one of the following:

IMGS-619
Radiometry
Credits 3
This course is focused on the fundamentals of radiation propagation as it relates to making quantitative measurements with imaging systems. The course includes an introduction to common radiometric terms and derivation of governing equations with an emphasis on radiation propagation in both non-intervening and turbid media. The course also includes an introduction to detector figures of merit and noise concepts.
IMGS-620
The Human Visual System
Credits 3
This course describes the underlying structure of the human visual system, the performance of those structures and the system as a whole, and introduces psychophysical techniques used to measure them. The visual system's optical and neural systems responsible for collecting and detecting spatial, temporal, and spectral signals from the environment are described. The sources and extent of limitations in the subsystems are described and discussed in terms of the enabling limitations that allow practical imaging systems.

Admission Requirements

  • Complete the graduate application.
  • Hold a baccalaureate degree from an accredited institution (undergraduate studies should include the following: mathematics, through calculus and including differential equations; and a full year of calculus-based physics, including modern physics. It is assumed that students can write a common computer program)
  • Submit official transcripts (in English) of all previously completed undergraduate and graduate course work
  • Have a cumulative GPA of 3.0 or above (or evidence of relevant professional performance)
  • Submit a current resume
  • Submit a one- to two-page statement of educational objectives
  • Submit two letters of recommendation from individuals familiar with the applicant’s academic or research capabilities
  • Submit scores from the Graduate Record Exam (GRE)
  • A test of English Language aptitude (TOEFL) is required of all applicants and course registrants whose native language is not English. Applicants are exempt from submitting exams if they have worked or studied in the U.S. for the last two years or they are from countries and attended universities whose native language is English.

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