Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles

Frontiers in Neuroscience
Xiaoying TangMichael I Miller

Abstract

We propose a hierarchical pipeline for skull-stripping and segmentation of anatomical structures of interest from T1-weighted images of the human brain. The pipeline is constructed based on a two-level Bayesian parameter estimation algorithm called multi-atlas likelihood fusion (MALF). In MALF, estimation of the parameter of interest is performed via maximum a posteriori estimation using the expectation-maximization (EM) algorithm. The likelihoods of multiple atlases are fused in the E-step while the optimal estimator, a single maximizer of the fused likelihoods, is then obtained in the M-step. There are two stages in the proposed pipeline; first the input T1-weighted image is automatically skull-stripped via a fast MALF, then internal brain structures of interest are automatically extracted using a regular MALF. We assess the performance of each of the two modules in the pipeline based on two sets of images with markedly different anatomical and photometric contrasts; 3T MPRAGE scans of pediatric subjects with developmental disorders vs. 1.5T SPGR scans of elderly subjects with dementia. Evaluation is performed quantitatively using the Dice overlap as well as qualitatively via visual inspections. As a result, we demonstrate su...Continue Reading

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Citations

Mar 25, 2016·Hippocampus·Vijay R VarmaMichelle C Carlson
Jun 8, 2017·Journal of Magnetic Resonance Imaging : JMRI·Yuanyuan QinWenzhen Zhu
Jan 1, 2015·Magnetic Resonance Insights·Anwar S ShatilChase R Figley
Oct 31, 2018·Human Brain Mapping·Xiaoying TangMichael I Miller
May 14, 2019·Neurorehabilitation and Neural Repair·Gang LiuJinsheng Zeng
May 14, 2016·Restorative Neurology and Neuroscience·Rajani SebastianArgye E Hillis
Jun 12, 2018·Otology & Neurotology : Official Publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology·Rebecca J KamilYuri Agrawal
Sep 5, 2019·Brain and Behavior·Thiago J R RezendeAndreia V Faria
Dec 26, 2018·NeuroImage. Clinical·Raphael F CassebMarcondes C França Junior
Jul 19, 2019·Magnetic Resonance Imaging·Chin-Fu LiuUNKNOWN Alzheimer's Disease Neuroimaging Initiative
Apr 4, 2021·The Laryngoscope·Andrew YousefSteven W Cheung

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Software Mentioned

MIPAV
Freesurfer
ANTS
MIPAV ( Medical Image Processing , Analysis , and Visualization )
STAPLE
Brain Extraction Tool ( BET )
HWA
MriCloud
FSL
XSEDE

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