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Project: Automated extraction of the dentato-rubro thalamic tract

Description

The proposed master project aims to provide an overview of automated methods for the detection of the AC-PC line in medical imaging and segmentation approaches for the extraction of the dentato-rubro thalamic tract (DRTT) using diffusion MRI tractography. Both the AC-PC line and the DRTT are essential in neuroimaging research and clinical treatment for motor disorders. The project will explore the existing automated methods for detecting the AC-PC line, including atlas-based approaches and machine learning-based methods. The advantages and limitations of each approach will be compared, and the potential for future developments will be discussed.

In the second part of the project, the focus will be on segmentation approaches for the DRTT using diffusion MRI tractography. The aim is to develop new methods and algorithms for segmenting the DRTT, which can help in the diagnosis and treatment of movement disorders. The project will investigate the existing approaches for DRTT segmentation, including deterministic and probabilistic tractography, as well as advanced methods such as deep learning-based approaches. The proposed algorithms will be evaluated on a dataset of healthy controls and patients who undergo deep brain stimulation for the treatment of Parkinson's or essential tremor. The project will conclude with a discussion of the results and the potential for future research in this area.

Details

Student

ML

Miriam Laamoumi

Supervisor

Maxime Chamberland

Secondary supervisor

Tom Hendriks