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

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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