automated fetal brain segmentation from 2d mri slices for motion correction
TRANSCRIPT
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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
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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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