Paper Info
Title
Spacial Aliasing Artefact Detection On T1-Weighted Mri Images
Abstract
Magnetic Resonance Imaging (MRI) exams suffer from undesirable structure replicating and overlapping effects on certain acquisition settings. These are called Spatial Aliasing Artefacts (SAA) and their presence interferes with the segmentation of other anatomical structures. This paper addresses the segmentation of the SAA in T1-weighted MRI image sets, in order to effectively remove their influence over the legitimately positioned body structures. The proposed method comprises an initial thresholding, employing the Triangle method, an aggregation of neighboring voxels through Region Growing. Further refinement of the objects contour is obtained with Convex Hull and a Minimum Path algorithm applied to two orthogonal planes (Sagittal and Axial).Some experiments concerning the extension of the pipeline used are reported and the results seem promising. The average contour distance concerning the Ground Truth (GT) rounds 2.5mm and area metrics point out average overlaps above 64% with the GT. Some issues concerning the fusion between the output from the two planes are to be perfected. Nevertheless, the results seems sufficient to neutralize the influence of SAA and expedite the downstream anatomical segmentation tasks.
Year
DOI
Venue
2017
10.1007/978-3-319-58838-4_51
PATTERN RECOGNITION AND IMAGE ANALYSIS (IBPRIA 2017)
Keywords
Field
DocType
Segmentation, Aliasing, Minimum Path, MRI, T1-weighted
Voxel,Computer vision,Pattern recognition,Computer science,Segmentation,Convex hull,Aliasing,Artificial intelligence,Region growing,Thresholding,Sagittal plane,Magnetic resonance imaging
Conference
Volume
ISSN
Citations 
10255
0302-9743
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
João F. Teixeira100.68
Hélder P. Oliveira26313.99