Special Topics CAP5937-Medical Image Computing (SPRING 2016)

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Instructor: Prof. Ulas Bagci    

Class time: Monday/Wednesday 10.30-11.45 am
Class location: HPA1 0106
Office hours: Monday/Wednesday 3-5 pm

COURSE GOALS: Imaging science is experiencing tremendous growth in the US. The New York Times recently ranked biomedical jobs as the number one fastest growing career field in the nation and listed bio-medical imaging as a primary reason for the growth. Biomedical imaging and its analysis are fundamental to understanding, visualizing, and quantifying medical images in clinical applications. With the help of automated and quantitative image analysis techniques, disease diagnosis will be easier/faster and more accurate, and leading to significant development in medicine in general. The goal of this course is to help students develop skills in computational radiology, radiological image analysis, and biomedical image processing fields. The following topics will be covered:
PRE-REQUEST: Basic Probability/Statistics, a good working knowledge of any programming language (python, matlab, C/C++, or Java), Linear algebra, Vector calculus.

GRADING:Assignments and mini projects should include explanatory/clear comments as well as a short report describing the approach, detailed analysis, and discussion/conclusion. RECOMMENDED BOOKS (optional) PROGRAMMING
Students are enocouraged to use ITK/VTK programming libraries in implementation of the programming assignments and project.
ITK is an open-source, cross-platform system that provides developers with an extensive suite of software tools for image analysis.
The Visualization Toolkit (VTK) is an open-source, freely available software system for 3D computer graphics, image processing, and visualization. It consists of a C++ class library and several interpreted interface layers including Tcl/Tk, Java, and Python.

Python and/or C/C++ can call functions of ITK/VTK easily. Matlab can be used for assignments as well.
Following book (Python programming samples for computer viion tasks) is freely available.
Python for Computer Vision

Collaboration on assignments is encouraged at the level of sharing ideas and technical conversation only. Please write your own code. Students are expected to abide by UCF Golden Rule.





will be updated soon...


[Ulas Bagci in 2015]
Ulas Bagci in 2009
Name: Ulas Bagci
URL: http://www.cs.ucf.edu/~bagci
Work number: (+1) 407-823-1047
Fax number: (+1) 407-823-0594
CRCV Assistant: Tonya LaPrarie
Mailing address: Dr. Ulas Bagci
Center for Research in Computer Vision (CRCV)
4328 Scorpius Street, HEC 221, UCF

Orlando, Florida 32816, USA.

Last updated September, 2015 by Ulas Bagci.