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Intelligent Multimedia Processing
Laboratory
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2010 Medical Informatics Workshop |
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AGENDA
Session descriptions
1. Introduction to Medical Informatics (9:15-9:45am – Dr. Daniela Raicu)
Description: Biomedical Informatics is an emerging discipline that has been
defined as the study, invention, and implementation of structures and
algorithms to improve communication, understanding and management of medical
information. In this talk we will introduce the main concepts and fields of
medical informatics, the courses and research labs from CDM that are
relevant to medical informatics, and what kind of jobs people in medical
informatics have.
2. Medical Informatics Research at CDM (9:45-10:45am – Dr. Jacob Furst)
Description: Computer science can be a valuable tool for practicing
medicine. In particular, applications of computer aided diagnosis and
detection provide assistance to medical practitioners that can increase
reliability and efficiency, and decrease the rate of false positives without
subsequently increasing the rate of false negatives. We will discuss some of
the projects that we have been involved with in the area of medical
informatics – we will motivate the medical problems, describe how
algorithmic ideas like image processing and computer learning are
applicable, and discuss our own results.
3. The MedIX Program at DePaul University and University of Chicago
(11:00-11:30am – Dr. Daniela Raicu)
Description: The Medical Informatics lab has a well-known tradition of
hosting undergraduate research during the academic year and the summer
through funded opportunities by CDM, DePaul and NSF. We will describe our
NSF REU program and present statistics on student success over 2005-2010.
4. Hands-on experience with medical images (12-12:50pm – Dmitriy Zinovev)
Description: A Matlab tutorial on how to process medical images and identify
tumors will be offered in CDM801 lab. Student will visualize Computed
Tomography images of the chest and look for lung nodules in a publically
available dataset provided by NIH. Students will learn how to read and write
these images in Matlab, learn about pixel data and how it can be connected
to the lung nodule interpretation. |
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