ATLAS-BASED SEGMENTATION OF ULTRAHIGH-RESOLUTION STRUCTURAL MR HEAD IMAGES ACQUIRED AT 7 TESLA
ATLAS-BASED SEGMENTATION OF ULTRAHIGH-RESOLUTION STRUCTURAL MR HEAD IMAGES ACQUIRED AT 7 TESLA
Abstract
Purpose: The purpose of this work was to find out how the existing brain atlases and
segmentation algorithms perform when applied to ultrahigh-resolution MR brain
images, acquired with a 7-Tesla scanner. Also to make adaptations to deal with the
potential challenges and evaluate the quality of the anatomical segmentations of the 7-
Tesla images.
Materials: A dataset of MR brain images with various resolutions (1mm, 500 m, 250 m non averaged & 250 m averaged) shared by Lüsebrink et al. from the 7 Tesla scanner in
Magdeburg was used.
Methods: Two atlas-based anatomical image segmentation algorithms were applied: Pincram for
brain extraction and MAPER for labelling multiple brain regions. The resulting brain
masks and label maps were assessed qualitatively and quantitatively. Visual evaluation
of the quality of the segmentations was made by the auther and external experts. To
quantify the consistency of segmentations at the highest resolution, the Jaccard overlap
coefficient were calculated.
Shape base averaging (SBA) has been implemented on the MAPER-segmented atlases
and applied to a 500 m resolution image to improve the appearance of the
segmentation. It was then compared to Vote Rule decision Fusion (VRF) that is the
standard method of fusing atlas labels in MAPER.
Conclusion: MAPER and Pincram work on brain images obtained with a 7-Tesla scanner even
though the algorithms have been designed for and validated on 1.5 and 3 Tesla. The
data size at the highest resolution exceed available computational resources, therefore
images had to be downsampled to 500 m.
The segment boundaries were smoother with SBA than with VRF and they got more
pleasant to look at. Some boundaries do get misplaced, so the volume estimation of the
structures might not be better than with VRF.
Degree
Student essay
Collections
View/ Open
Date
2022-01-13Author
Johansson, Frida
Keywords
Medical physics
Anatomical segmentation
Brain
MRI
7 Tesla
Pincram
MAPER
Shape based averaging
Ultrahigh resolution
Language
eng