ELECTRONIC POSTER - ismrm

egularization parameter is adapted automatically based on the details in the images, which improves the reconstruction of details as
well as providing an adequate smoothing for the homogeneous parts.
15:00 5089. Modeling Non-Central Chi Distributed Noise in T1-Weighted MR Images: Brain
Tissue Segmentation Using Partial Volume Densities
Hugo Gerard Schnack 1 , Rachel Brouwer 1 , Hilleke Hulshoff Pol 1
1 Psychiatry, UMC Utrecht, Utrecht, Netherlands
A brain tissue segmentation algorithm is developed that includes a non-central Chi description of the MR scanner noise. It is applied
to a set of MR images of 16 healthy human volunteers and found to produce significantly different tissue volume estimates, when
compared to models incorporating Gaussian noise.
15:30 5090. Automatic Quality Assessment for Multi-Slice 2D FLAIR MR Imaging
Bénédicte Mortamet 1 , Matt A. Bernstein 2 , Clifford R. Jack 2 , Jeffrey L. Gunter 2 , Maria
Shiung 2 , Reto Meuli 3 , Jean-Philippe Thiran 4 , Gunnar Krueger 1
1 Advanced Clinical Imaging Technology, Siemens Healthcare Sector IM&WS S - CIBM, Lausanne,
Switzerland; 2 Mayo Clinic, Rochester, MI, United States; 3 CHUV, Radiology, Lausanne, Switzerland; 4 Signal
Processing Laboratory (LTS5) Ecole Polytechnique Fédérale de Lausanne
The FLAIR contrast is increasingly used as part of routine protocol for brain MRI. It provides high sensitivity to a wide range of
disease but is susceptible to patient motion. Resulting artifacts may obscure the pathology or mislead automated image analysis
algorithms. We propose a method that automates quality classification of T2w 2D-FLAIR data. The validation based on 99 head scans
confirms the robustness and reliability of the method. It could greatly improve clinical workflow as, in particular if integrated in online
image reconstruction, it could provide immediate feedback to the MR technologist to repeat low-quality scans within the same session.
Tuesday 13:30-15:30 Computer 125
13:30 5091. A Fully Automatic Cerebellum Segmentation Method Using an Active Contour
Model with Shape Prior
Jinyoung Hwang 1 , Junmo Kim 1 , HyunWook Park 1
1 Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea,
Republic of
The segmentation of cerebellum in human brain is not widely used since the boundary between cerebrum and cerebellum is
indistinguishable due to the partial volume effect. Although some literatures proposed the methodology in cerebellum segmentation,
they are not the purpose of the cerebellum segmentation. In this work, we present fully automatic cerebellum segmentation method
using shape priors in brain MR images, which already skull-stripped volume. We evaluated the proposed method to images from
BrainWeb, 1.5T, and 3T MR scanner. The proposed method shows fine segmentation results, and it could be used for cerebellum
generation in human brain.
14:00 5092. A Fully Automated White Matter / Gray Matter Segmentation of Mice Spinal Cord
on DTI Images
Michaël Sdika 1 , Virginie Callot 1 , Mathias Hebert 1 , Guillaume Duhamel 1 , Patrick J.
Cozzone 1
1 CRMBM/CNRS UMR6612, Faculté de médecine, Université de la Méditérranée, Marseille, France, France
In this work, a fully automated method is proposed to segment mice SC white matter (WM) and gray matter (GM) tissues on
Diffusion Tensor Imaging (DTI) images. The proposed method is based on three main step: first a small patch containing the SC is
detected using a machine learning procedure, then a mask of the SC is computed within this patch and finally WM/GM segmentation
is performed. Specific attention has been paid to choose an appropriate modality for each steps. The segmentation results has been
evaluated by visual assessment by two experts on the images of 13 mice.
14:30 5093. Extracellular Fluid Volume Measurements with Complex Signal Analysis
John David Dickson 1 , Guy Barnett Williams 2 , Thomas Adrian Carpenter 2 , Richard E.
Ansorge 1
1 Department of Physics, Cambridge University, Cambridge, Cambridgeshire, United Kingdom; 2 Wolfson Brain
Imaging Centre, Cambridge University, Cambridge, Cambridgeshire, United Kingdom
It has been suggested that extracellular fluid spins undergo bulk dephasing from those in intracellular fluid. This study provides direct
evidence for this phenomenon and exploits it to make quantitative measurements of both the intra/extracellular fluid volume fractions
and precession frequencies. This is achieved by fitting the data from a Gradient Echo Sampling of a Free Induction Decay (GESFID)
sequence with a complex signal model.