Register now After registration you will be able to apply for this opportunity online.
Machine Learning-Based Automated Analysis of Murine Brain Corrosion Casts
This project aims to investigate the use of machine learning-based algorithms to obtain a deeper understanding of the graph-structured vasculature preserved in corrosion casts. For a more detailed description, please refer to the attached document.
Keywords: Neuroscience, Brain Vasculature, Medical AI, Machine Learning, Network Analysis, Biomedical Image Analysis, Whole Brain Analysis, Deep Learning, Computer Vision
The brain is one of the most complex organs in the human body. Its proper functioning relies heavily on a vast network of blood vessels known as the brain vasculature. The brain vasculature is not only responsible for delivering oxygen and nutrients to the brain's neurons and removing waste products but also plays a critical role in regulating cerebral blood flow and maintaining the blood-brain barrier. Therefore, obtaining a deeper understanding of the brain vasculature's structure and function is essential to study human intelligence and to gain insights into various neurological disorders, such as stroke, dementia, and brain tumors.Recent advances in imaging technologies have enabled researchers to study the whole brain vasculature in unprecedented detail. In this context, a promising approach is represented by transforming brain vasculature into graph-structured data consisting of blood vessels (edges) and their bifurcation points (vertices).
The brain is one of the most complex organs in the human body. Its proper functioning relies heavily on a vast network of blood vessels known as the brain vasculature. The brain vasculature is not only responsible for delivering oxygen and nutrients to the brain's neurons and removing waste products but also plays a critical role in regulating cerebral blood flow and maintaining the blood-brain barrier. Therefore, obtaining a deeper understanding of the brain vasculature's structure and function is essential to study human intelligence and to gain insights into various neurological disorders, such as stroke, dementia, and brain tumors.Recent advances in imaging technologies have enabled researchers to study the whole brain vasculature in unprecedented detail. In this context, a promising approach is represented by transforming brain vasculature into graph-structured data consisting of blood vessels (edges) and their bifurcation points (vertices).
The aim of this project is to use and develop novel (potentially ML-based) algorithms to obtain a deeper understanding of the graph-structured vasculature preserved in corrosion casts.
To this end, potential projects include whole-brain quantitative analysis, graph neural networks, and/or novel graph-based clustering approaches.
The aim of this project is to use and develop novel (potentially ML-based) algorithms to obtain a deeper understanding of the graph-structured vasculature preserved in corrosion casts.
To this end, potential projects include whole-brain quantitative analysis, graph neural networks, and/or novel graph-based clustering approaches.
Please refer to the attached document. We are looking forward hearing form you!
Please refer to the attached document. We are looking forward hearing form you!
cc_proposal.pdf
