automated fetal brain segmentation from 2d mri slices for motion correction
TRANSCRIPT
Automated Fetal Brain Segmentation from 2DMRI Slices for Motion Correction
Kevin Keraudren, Maria Murgasova, Vanessa Kyriakopoulou,Christina Malamateniou, Mary Rutherford, Bernhard Kainz,
Jo Hajnal & Daniel Rueckert
October 7th, 2014
Imaging the fetus using MRI
As the fetuse moves
the data is acquired as stacks of misaligned 2D slices
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Motion correction of fetal brain MRIorthogonal stacks
of 2D slices3D volume
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Box detection
MSER Size filtering Bag-of-SIFT RANSAC
MSER regionsFiltering by size and Bag-of-Words
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Box detection
Brain and non-brain patches are learnt from the detected box and itsMSER regions
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Brain extractionRandom Forest classifier
and Conditional Random Field
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Motion correction
Adapted from Kuklisova-Murgasova et al., 2012.
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Motion correctionConditional Random Field
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Results
Automatedsegmentation
A B C
Man
ual
segm
enta
tion A 42 3 0
B 2 8 5
C 0 1 5
A. no evident artefacts from motionB. minor artifacts but can still be used for diagnosisC. cannot be used for clinical diagnosis
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Results“In 85% of the tested cases, our proposed method produced a motion
corrected volume of a relevant quality for clinical diagnosis.”
NeuroImage, 2014.
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Results
Tighter mask, less artifactsand brain already extracted
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Code
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Code
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Thanks!
www.doc.ic.ac.uk/~kpk09
kevin-keraudren.blogspot.co.uk
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