ELECTRONIC POSTER - ismrm

14:30 5113. Dipole Matched Filter with SWIFT
Curtis Andrew Corum 1,2 , Djaudat Idiyatullin 1 , Steen Moeller 1 , Ryan Chamberlain 1 ,
Michael Garwood 1,2
1 Center for Magnetic Resonance Research, Dept. of Radiology, Medical School, University of Minnesota,
Minneapolis, MN, United States; 2 Cancer Center, Medical School, University of Minnesota, Minneapolis, MN,
United States
The combination of the SWIFT sequence and a secular dipole matched filter give positive contrast at dipole sites.
15:00 5114. Forward-Field Calculations Improve Contrast of Unwrapped MR Phase Images
Martijn D. Steenwijk 1 , Maarten J. Versluis 2 , Mark A. van Buchem, Johan H C Reiber 1 ,
Andrew Webb 2 , Julien Milles 1
1 Division of Image Processing, Leiden University Medical Center, Leiden, Zuid-Holland, Netherlands; 2 CJ
Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, Zuid-
Holland, Netherlands
The aim of this work is to evaluate the gray matter / white matter (GM/WM) contrast improvement obtained by using forward-field
calculations when unwrapping MR phase images of the brain. Standard phase unwrapping methods, such as high-pass filtering, prove
sub-optimal in eliminating phase wraps with high spatial frequencies. Forward-field calculations can be used to compute geometrydependent
artifact-corrected (GDAC) images in which the residual phase wrapping is reduced significantly. We applied this technique
to a high-resolution T2*-weighted sequence at 7T to study its effects on GM/WM contrast. The GDAC technique results in a more
favourable trade-off between unwrapping and GM/WM contrast.
Thursday 13:30-15:30 Computer 126
13:30 5115. Segmentation of the Structure of the Mouse 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 the sub-structures of the mouse spinal Cord. WM/GM segmentation is
used as input of the proposed method and on output, the GM substructures are distributed in Left Ventral and Dorsal GM and Right
ventral and dorsal GM whereas substructures of WM were distributed into Left Lateral WM, Right Lateral WM, Ventral WM and
Dorsal WM. The method has been evaluated by visual assessment and correlation with manual segmentation on 10 DTI images of
mice acquired at 11.75T and show promising results.
14:00 5116. Longitudinal Changes of White Matter Lesions
Snehashis Roy 1 , Aaron Carass 1 , Navid Shiee 1 , Dzung L. Pham 2 , Susan Resnick 3 , Jerry L.
Prince 1,2
1 Electrical and Computer Engg, Johns Hopkins University, Baltimore, MD, United States; 2 Department of
Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, United States; 3 Laboratory of
Personality and Cognition, National Institute on Aging, Baltimore, MD, United States
Progression of white matter lesions are important for early detection and monitoring of diseases like Alzheimer's or Multiple Sclerosis.
FLAIR images provide superior contrast for lesions compared to traditional T1 or T2 weighted images. But they are often not acquired
for time and cost constraints. We developed an atlas based method to synthesize FLAIR images from T1 and T2 acquisitions. We use
this method to quantify the progression of lesions on a pool of 20 subjects. Synthesizing FLAIRs can be seen as a potential way to
reduce unnecessary data acquisition.
14:30 5117. Accurate Adipose Tissue Segmentation from Single Gradient Echo Phase Images by
Adaptive Local Thresholding
Christian Würslin 1 , Frank Eibofner 1 , Fabian Springer 1 , Fritz Schick 1
1 Department of Diagnostical and Interventional Radiology, Section on Experimental Radiology, University
Hospital Tübingen, 72076 Tübingen, Germany
In many applications, a quantification of fat is desired. Most (semi-)automatic procedures use T1-weighted spin echo images to
accomplish this. These approaches are time-consuming and a precise quantification is usually complicated by a high amount of partial
volume effects. We propose a quantification procedure based on one single phase image, acquired with a gradient echo technique and
opposed-phase condition. This maximizes the contrast in between fat- and water- dominated tissues and is less time-consuming. The
phase divergence, arising from inhomogeneities, is compensated for using an automated algorithm, enabling a precise fat
quantification by thresholding. Phantom measurements show a high precision.
15:00 5118. Improving Robustness of Cartilage Segmentation Using IDEAL Water and Fat
Images
Raghu Kokku 1
1 MR SW & Apps , GTO-I, Wipro GE Healthcare, Bangalore, Karnataka, India
Accurate and reliable quantification of cartilage volume in MRI is required for diagnosis of many degenerative and inflammatory
diseases such as osteoarthritis or rheumatoid arthritis. A Novel approach to segment the anatomical structures and cartilage using