Segmentation

Multimodal spine multiple sclerosis segmentation

May 16, 2025

This project presents an open-source pipeline for segmenting multiple sclerosis lesions in the spinal cord using multimodal MRI data. Built for the MS-Multi-Spine Challenge, it combines nnUNet, the Spinal Cord Toolbox, Docker, and Boutiques for reproducibility and ease of use. The pipeline includes preprocessing, inference, and post-processing steps, and is packaged with full documentation and containerization to support future research and clinical applications in spinal cord imaging.

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.

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

January 1, 0001

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.

Multimodal spine multiple sclerosis segmentation

Spinal Cord Segmentation Generalizable Across Datasets

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

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