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

2/16

3/16

4/16

Motion correction of fetal brain MRIorthogonal stacks

of 2D slices3D volume

5/16

Box detection

MSER Size filtering Bag-of-SIFT RANSAC

MSER regionsFiltering by size and Bag-of-Words

6/16

Box detection

Brain and non-brain patches are learnt from the detected box and itsMSER regions

7/16

Brain extractionRandom Forest classifier

and Conditional Random Field

8/16

Motion correction

Adapted from Kuklisova-Murgasova et al., 2012.

9/16

Motion correctionConditional Random Field

10/16

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

11/16

Results“In 85% of the tested cases, our proposed method produced a motion

corrected volume of a relevant quality for clinical diagnosis.”

NeuroImage, 2014.

12/16

Results

Tighter mask, less artifactsand brain already extracted

13/16

Code

14/16

Code

15/16

Thanks!

www.doc.ic.ac.uk/~kpk09

kevin-keraudren.blogspot.co.uk

16/16