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Automated segmentation and motion correction of the fetal brain

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Information about Automated segmentation and motion correction of the fetal brain
Technology

Published on March 2, 2014

Author: kevinkeraudren

Source: slideshare.net

Description

For more details on these slides, visit: http://kevin-keraudren.blogspot.co.uk/2014/03/xkcd-style-beamer-presentation-latex.html
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Automated segmentation and motion correction of the fetal brain Kevin Keraudren Imperial College London December 6th , 2013

Problem As the fetuse moves the data is acquired as stacks of misaligned 2D slices 2/12

Problem orthogonal stacks of 2D slices 3D volume 3/12

Definitions recall = Volume of correctly classified voxels Ground truth volume of the brain recall = precision = TP TP + FN Volume of correctly classified voxels Detected volume of the brain precision = TP TP + FP 4/12

Idea 100 80 91% 99% 93% 96% 60 recall precision 40 20 0 Box detection RF/CRF Enlarged Final segmentation segmentation segmentation 5/12

Box detection MSER MSER regions Size filtering Bag-of-SIFT RANSAC Filtering by size and Bag-of-Words 6/12

Box detection 7/12

Brain extraction Random Forest classifier and Conditional Random Field 8/12

Motion correction Slice to volume registration Volume registration Automated masking Acquisition of snapshot images Update slices segmentation Robust statistics and superresolution Reconstructed volume 9/12

Motion correction Conditional Random Field 10/12

Result Tighter mask, less artifacts and brain already extracted 11/12

Acknowledgements Collaborators: Maria Murgasova, Vanessa Kyriakopoulou, Christina Malamateniou, Mary Rutherford, Bernhard Kainz, Jo Hajnal & Daniel Rueckert XKCD for Matplotlib, Latex and Tikz: Jake Vanderplas, Damon McDougall, Johannes Buchner, percusse www.doc.ic.ac.uk/~kpk09/ 12/12

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