Signals communicate information. Signal processing separates unimportant from important information in a signal to make relevant information easily accessible. Biomedical signal processing extracts useful information from biological signals, such as the pattern found in a CT scan. The goal is to eliminate noise from the signal by designing filters that best separate signal from noise. Identifying and measuring features that best characterize the information of interest in a signal is another goal of signal processing.
Who:
This workshop is aimed at graduate students and other researchers who would like to learn more about signal processing for image data. This workshop is open to those from neighboring institutions.
Prerequisite:
Basic competence with the Python programming language and the NumPy library.
Where:
Room 4320, 10 Discovery Drive, Farmington, Connecticut.
Get directions with
OpenStreetMap
or
Google Maps.
Requirements: Participants must bring a laptop with a
Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.). They should have the most recent version of
R and RStudio installed (see below).
Accessibility: We are committed to making this workshop
accessible to everybody.
The workshop organizers have checked that:
The room is wheelchair / scooter accessible.
Accessible restrooms are available.
Materials will be provided in advance of the workshop and
large-print handouts are available if needed by notifying the
organizers in advance. If we can help making learning easier for
you (e.g. sign-language interpreters, lactation facilities) please
get in touch (using contact details below) and we will
attempt to provide them.
Python is a popular language for
research computing, and great for general-purpose programming as
well. Installing all of its research packages individually can be
a bit difficult, so we recommend
Anaconda,
an all-in-one installer.
Regardless of how you choose to install it,
please make sure you install Python version 3.x
(e.g., 3.6 is fine).
We will teach Python using the Jupyter Notebook,
a programming environment that runs in a web browser (Jupyter Notebook will be installed by Anaconda). For this to work you will need a reasonably
up-to-date browser. The current versions of the Chrome, Safari and
Firefox browsers are all
supported
(some older browsers, including Internet Explorer version 9
and below, are not).
Download the Anaconda for Windows installer with Python 3. (If you are not sure which version to choose, you probably want the 64-bit Graphical Installer Anaconda3-...-Windows-x86_64.exe)
Install Python 3 by running the Anaconda Installer, using all of the defaults for installation except make sure to check Add Anaconda to my PATH environment variable.
Download the Anaconda Installer with Python 3 for Linux.
(The installation requires using the shell. If you aren't
comfortable doing the installation yourself
stop here and request help at the workshop.)
Open a terminal window and navigate to the directory where
the executable is downloaded (e.g., `cd ~/Downloads`).
Type
bash Anaconda3-
and then press
Tab to autocomplete the full file name. The name of
file you just downloaded should appear.
Press Enter.
You will follow the text-only prompts.
To move through the text, press Spacebar.
Type yes and press enter to approve the license.
Press Enter to approve the default location
for the files.
Type yes and press Enter
to prepend Anaconda to your PATH
(this makes the Anaconda distribution the default Python).