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Analysis of fluorescence microscopy and structural MRI data using QuPath analysis software - *Peer2Peer* Spring Season, 2023

Analysis of fluorescence microscopy and structural MRI data using QuPath analysis software - *Peer2Peer* Spring Season, 2023 In-Person

Welcome to the Peer-to-Peer Teaching Spring Season 2023. These sessions are taught by our own community members to fill knowledge gaps and keep up with the accelerated pace at which bioinformatics grows as well as other data analysis methodologies. 

This session dedicated to image analysis with the free software QuPath will be taught by our colleague Zachary Gursky, Ph.D. who is a postdoctoral fellow in the department of Anesthesiology and Neuroscience. 

Description: 

In modern biology research, tremendous amounts of data are generated using diverse imaging methods such as fluorescence microscopy and magnetic resonance imaging. Many different analysis software has been created to generate quantitative data from these images (e.g., counting cell numbers, quantifying fluorescence intensity, determining the area fraction of tissue expressing a marker). The software "QuPath" (abbreviation of "Quantitative Pathology & Bioimage Analysis") is free, open-source, does not require coding experience, and can analyze many different image file types. Thus, QuPath is a versatile program that can be used in many different kinds of biological experiments, as is proven by its 2800+ citations since its development in 2017.

Join in the fun by learning how to analyze microscopy and MRI example images, and even try out QuPath on your own image data! During this interactive workshop, you will learn how to open and analyze image data in QuPath and will learn how to get other tutorials and online assistance for more advanced features (which there are tons of!). In addition to hands-on learning with example images, we will briefly discuss alternative software for image analysis to supplement QuPath's functions and will use any remaining time to answer questions about your own image data to help you get started.

This workshop is designed for:

biomedical researchers with an interest in quantitative image analysis of fluorescence microscopy or structural MRI image data. No coding experience is necessary.

You will learn how to:

  1. Open and organize images into a QuPath project.
  2. Automate cell number quantification and phenotyping of those cells in a fluorescence microscopy image.
  3. Use a machine-learning classifier to quantify the area fraction of different tissue types in an MRI image and a fluorescence microscopy image.
  4. Apply analyses to multiple images for reproducible science.
  5. Locate tutorials and online resources for advanced applications of QuPath beyond the functions covered in this workshop.

Requirements:

If you would like to participate in the hands-on analysis portion of this workshop, please do the following:

  1. Bring a computer with QuPath installed prior to the workshop. The current version (v0.4.3 as of March 13th, 2023) can be downloaded at https://qupath.github.io/.
  2. Make sure your computer has internet access if you would like to search/bookmark websites for tutorials and support during the workshop.
  3. Download the example images which will be distributed via email during the week prior to the workshop.
  4. If you would like to troubleshoot an image of your own, bring 1 fluorescence microscopy image or structural MRI image with a file size of <150MB. Larger file sizes may result in difficulty dues to increased processing time during the session.
  1. QuPath is compatible with an extensive list of image types (including TIFF and many proprietary formats such as CZI, LSM, OIR, and more). See https://qupath.readthedocs.io/en/stable/docs/intro/formats.html) for more information on whether your image data is currently in a format that can be opened and analyzed by QuPath.
Date:
Thursday, April 13, 2023 Show more dates
Time:
10:00am - 12:00pm
Time Zone:
Eastern Time - US & Canada (change)
Location:
SHM L 111, Cushing/Whitney Medical Library, 333 Cedar Street
Campus:
Medical School
Categories:
  Bioinformatics     Peer-to-Peer Teaching  
Registration has closed.

Event Organizer

Profile photo of Sofia Fertuzinhos
Sofia Fertuzinhos
Profile photo of Vermetha Polite
Vermetha Polite