Madelyn Corliss

Madelyn Corliss

Mentor

David Vaillancourt, PhD

College

College of Health and Human Performance

Major

Applied Physiology and Kinesiology

Minor

Disabilities in Society

Organizations

Executive Board of Panhellenic Council, Delta Gamma, Dance Marathon at UF

Academic Awards

N/A

Volunteering

Fit for All at GHF

Research Interests

Rehabilitation neuroscience for motor disorders and biomarkers of Parkinson's disease

Hobbies and Interests

Research Project

Evaluating Spatial Filtering on Diffusion MRI Data Harmonization in Parkinsonism

We are testing a spatial filtering procedure to harmonize the noise across diffusion MRI datasets from many different sites and scanner vendors in a cohort of patients with different forms of Parkinsonism. The rationale is to create an algorithm that distinguishes between the types of Parkinsonism across many different diffusion MRI sequences from different vendors. If it can differentiate between normal and atypical parkinsonism, the program could help decrease the number of misdiagnoses. Using the data from a 2019 study by Dr. Vaillancourt, “Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study,” about 1,000 participants will be processed with different full-width half maximum spatial filters. We will test no filter, 2mm, 4mm, and 6mm spatial filters on the data. This includes data from 8 cohorts internationally (including University of Florida, Penn State Hershey Medical Center, Medical University Innsbruck, Northwestern University, University of Michigan, Parkinson’s Progression Marker’s Initiative, and 4 Repeat Tauopathy Neuroimaging Initiative) totaling the use of 17 different MRI scanners. Introduction of a non-invasive biomarker can help improve rates and classifications of diagnoses in future research projects and eventually for physicians in a clinical setting. If physicians are able to upload the MRI imaging to the program, no matter the resolution, the impact could be felt worldwide. 

  • David Vaillancourt, PhD
  • Applied Physiology and Kinesiology
  • Disabilities in Society
  • Rehabilitation neuroscience for motor disorders and biomarkers of Parkinson's disease
  • N/A
  • Executive Board of Panhellenic Council, Delta Gamma, Dance Marathon at UF
  • Fit for All at GHF
  • Evaluating Spatial Filtering on Diffusion MRI Data Harmonization in Parkinsonism
  • We are testing a spatial filtering procedure to harmonize the noise across diffusion MRI datasets from many different sites and scanner vendors in a cohort of patients with different forms of Parkinsonism. The rationale is to create an algorithm that distinguishes between the types of Parkinsonism across many different diffusion MRI sequences from different vendors. If it can differentiate between normal and atypical parkinsonism, the program could help decrease the number of misdiagnoses. Using the data from a 2019 study by Dr. Vaillancourt, "Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study," about 1,000 participants will be processed with different full-width half maximum spatial filters. We will test no filter, 2mm, 4mm, and 6mm spatial filters on the data. This includes data from 8 cohorts internationally (including University of Florida, Penn State Hershey Medical Center, Medical University Innsbruck, Northwestern University, University of Michigan, Parkinson’s Progression Marker’s Initiative, and 4 Repeat Tauopathy Neuroimaging Initiative) totaling the use of 17 different MRI scanners. Introduction of a non-invasive biomarker can help improve rates and classifications of diagnoses in future research projects and eventually for physicians in a clinical setting. If physicians are able to upload the MRI imaging to the program, no matter the resolution, the impact could be felt worldwide.