Faculty
Electrical and Computer Engineering
Supervisor Name
Roy Eagleson
Keywords
Image Segmentation, MRI, Brain, VR, Slicer3D
Description
The goal for this project was to successfully segment a fetal brain scan (fetal scan) using the algorithms provided by the program Slicer3D. To better understand the hurdles that arose when segmenting a fetal scan, we first look at the segmentation of an adult brain scan. This will allow us to see the straightforward nature of a brain segmentation when a high quality, high resolution volume with distinct structures is available. After examining the adult brain scan, attention will be moved to the segmentation of the fetal scan, where we’ll first look at the algorithms used and methods followed. Finally the outcomes and issues of the segmentations of the fetal scans and their corresponding algorithms will be discussed.
Acknowledgements
I would like to acknowledge the help of my supervisor Dr. Roy Eagleson, as well as members of our research group, specifically co-supervisior Dr. Sandrine De Ribaupierre.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Document Type
Poster
Included in
Evaluating Algorithms Used For Fetal Brain Scan Segmentation
The goal for this project was to successfully segment a fetal brain scan (fetal scan) using the algorithms provided by the program Slicer3D. To better understand the hurdles that arose when segmenting a fetal scan, we first look at the segmentation of an adult brain scan. This will allow us to see the straightforward nature of a brain segmentation when a high quality, high resolution volume with distinct structures is available. After examining the adult brain scan, attention will be moved to the segmentation of the fetal scan, where we’ll first look at the algorithms used and methods followed. Finally the outcomes and issues of the segmentations of the fetal scans and their corresponding algorithms will be discussed.