mri

Grandpa is moody, will his cognition decline? Predicting cognitive decline in Parkinson's disease from non-motor symptoms evolution

June 21, 2024

While Parkinson’s disease (PD) is recognized by its motor symptoms, it is also characterized by non-motor symptoms (NMS), such as anxiety, depression, pain, etc. NMS often precede cognitive decline, making them potential predictors of such decline. This project aims to investigate the longitudinal association between non-motor symptoms and cognitive and neural decline in patients with PD. Early identification of individuals at higher risk of cognitive decline through their NMS presentation can facilitate timely interventions.

Spinal Cord Segmentation Generalizable Across Datasets

May 19, 2023

My idea is to train a deep learning model on multiple (4) spinal cord segmentation datasets to improve generalizability to new contrasts, vendors, pathologies, etc… My project aims to train the nnU-Net model architecture, a state-of-the-art deep learning architecture for biomedical segmentation, on four aggregated datasets and compare its generalizability capabilities with the four specific models trained on each individual dataset. I will conclude by comparing the two approaches on a fifth and sixth dataset outside of the training domain.

Twin normative modelling project

July 22, 2022

In this project I am trying to train and test a normative model on a neuroimaging data set containing twin longitudinal data. I want to look at both changes of deviations in z-scores over time and differences in z-scores between twins

Harmonizing Multisite MRI Data Using ComBat

May 16, 2020

Multisite data is becoming increasingly common in MRI-based studies with the proliferation of open datasets. This brings the benefit of increased statistical power, but there is a pitfall: increased variability due to site-specific effects. This project evaluates three methods of harmonizing multi-site data.

Brain Tumor Segmentation via SAM-based fine-tuning on structural MRI images

This project is to learn how to perform brain tumor segmentation using fine-tuning on foundation models, I followed tutorials provided by MedSAM and perform fine-tuning on open datasets.

Grandpa is moody, will his cognition decline? Predicting cognitive decline in Parkinson's disease from non-motor symptoms evolution

Spinal Cord Segmentation Generalizable Across Datasets

Twin normative modelling project

Harmonizing Multisite MRI Data Using ComBat

Brain Tumor Segmentation via SAM-based fine-tuning on structural MRI images

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