ELECTRONIC POSTER - ismrm

15:00 4016. Application of Rotational Tensor Interpolation to Tractography
Marta Morgado Correia 1,2 , Guy B. Williams 2
1 MRC Cognition and Brain Sciences Unit, Cambridge, Cambridgeshire, United Kingdom; 2 Wolfson Brain
Imaging Centre, Cambridge, Cambridgeshire, United Kingdom
Diffusion MRI was the first imaging modality to allow the visualization of white matter fibre paths in vivo, and non-invasively.
Tensor interpolation methods have often been used to improve the reproducibility and reliability of tractography results.
In this abstract we will introduce a new method for 3D tensor interpolation based on work by Batchelor and colleagues, and use
simulated data to compare its performance to well established methodologies.
Wednesday 13:30-15:30 Computer 57
13:30 4017. Identification of Corresponding Tracks in Diffusion MRI Tractographies
Eleftherios Garyfallidis 1,2 , Matthew Brett 3 , Vassilis Tsiaras 4 , George Vogiatzis 5 , Ian
Nimmo-Smith 1
1 MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom; 2 University of Cambridge, Cambridge,
United Kingdom; 3 University of California, Berkeley, United States; 4 Department of Computer Science,
University of Crete, Greece; 5 Computer Vision Group, Toshiba Research Europe, Cambridge, United Kingdom
Identifying manually corresponding tracks in different brain tractogaphies is a very complicated task, typically requiring lots of
expertise, and lots of time. Moreover different local diffusion models and different tractography algorithms generate tractographies
with wide differences in numbers of tracks and in shape characteristics. We address these problems by introducing an automatic
method for detecting corresponding tracks in different dMRI (diffusion weighted MRI) datasets.
14:00 4018. Automatic Tractography Segmentation by Morphological Continuity Clustering
Fang-Cheng Yeh 1 , Wen-Yih Isaac Tseng 2
1 Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States; 2 Center
for Optoelectronic Biomedicine, National Taiwan University College of Medicine, Taipei, Taiwan
We present a tractography segmentation algorithm called morphological continuity clustering (MCC), which is a fully automatic,
unguided method that clusters fiber tracts without predefining the cluster number. This algorithm is based on the concept that the
fibers of the same cluster share the morphological continuity, a feature used to determine whether two tracts should be grouped. The
performance was evaluated on tractography with a total of 100,000 fibers tracts generated by streamline tracking method on
generalized q-space imaging (GQI). The results showed that MCC is able to generate several clusters that correspond to well-known
fiber tracts. Further study is needed to improve the accuracy and robustness of the proposed method.
14:30 4019. False Positive Detection Using Filtered Tractography
Yogesh Rathi 1,2 , James Malcolm, 23 , Sylvain Bouix 1 , C-F Westin 4 , Martha E. Shenton 1,5
1 Psychiatry, Harvard Medical School, Boston, MA, United States; 2 Georgia Institute of Technology, Atlanta,
GA, United States; 3 Brigham and Women's Hospital, United States; 4 Radiology, Harvard Medical School,
Boston, MA, United States; 5 VA Clinical Neuroscience Division, Boston, MA, United States
Existing methods perform model estimation independently at each voxel and tractography is performed in the next step. We use a
nonlinear Kalman filter for simultaneous model estimation and tractography. The method not only provides an estimate of the model
parameters, but also a confidence in the estimation in terms of the covariance matrix. We utilize measures derived from this
covariance matrix to detect false positives in the tracts generated.
15:00 4020. Systematic Assessment of Effects of Noise and Resolution on Metrics of DTI
Tractography
Virendra Radheshyam Mishra 1,2 , Xin Fan 2 , Hao Huang 3,4
1 Biomedical Engineering, The University of Texas at Arlington , Arlington, TX, United States; 2 Advanced
Imaging Research Center, The University of Texas Southwestern Medical Center , Dallas, TX, United States;
3 Advanced Imaging Research Center, The University of Texas Southwestern Medical Center , Dallas, TX,
United States; 4 Department of Radiology, The University of Texas Southwestern Medical Center , Dallas, TX,
United States
Fiber volume and fiber count are two important metrics derived from DTI tractography. However, no systematic description of the
relationship between these two measures and noise or resolution has been reported so far. In this study, we measured fiber count and
fiber volume of left cingulum with DTI datasets of different SNR and resolution. Our results indicate that resolution plays a more
important role on both measures than SNR. With a normal range of SNR, both measures are almost constant for a normal resolution.
Compared to fiber count, fiber volume is a more stable measure.
Thursday 13:30-15:30 Computer 57
13:30 4021. SWI-Informed Diffusion Tensor Tractography
Michiel Kleinnijenhuis 1,2 , Markus Barth 1,3 , Daniel C. Alexander 4 , Anne-Marie van
Cappellen van Walsum 2,5 , David Gordon Norris 1,3
1 Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands;
2 Department of Anatomy, University Medical Centre St. Radboud, Nijmegen, Netherlands; 3 Erwin L. Hahn