Publications

2017
Song Y, Zhang F, Li Q, Huang H, O'Donnell LJ, Cai W. Locally-Transferred Fisher Vectors for Texture Classification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2017 p. 4912–4920.
Otake Y, Yokota F, Fukuda N, Takao M, Takagi S, Yamamura N, O’Donnell LJ, Westin C-F, Sugano N, Sato Y. Patient-Specific Skeletal Muscle Fiber Modeling from Structure Tensor Field of Clinical CT Images. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham; 2017 p. 656–663.
Zhang F, Wu W, Ning L, McAnulty G, Waber D, Gagoski B, Sarill K, Hamoda H, Song Y, Cai W, Rathi Y, O'Donnell LJ. Supra-threshold Fiber Cluster Statistics for Data-driven Whole Brain Tractography Analysis. In: International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 2017 p. 556-565.Abstract
Abstract. This work presents a supra-threshold fiber cluster (STFC) analysis that leverages the whole brain fiber geometry to enhance statistical group difference analysis. The proposed method consists of (1) a study-specific data-driven tractography parcellation to obtain white matter (WM) tract parcels according to the WM anatomy and (2) a nonparametric permutation-based STFC test to identify significant differences between study populations (e.g. disease and healthy). The basic idea of our method is that a WM parcel’s neighborhood (parcels with similar WM anatomy) can support the parcel’s statistical significance when correcting for multiple comparisons. The method is demonstrated by application to a multi-shell diffusion MRI dataset from 59 individuals, including 30 attention deficit hyperactivity disorder (ADHD) patients and 29 healthy controls (HCs). Evaluations are conducted using both synthetic and real data. The results indicate that our STFC method gives greater sensitivity in finding group differences in WM tract parcels compared to several traditional multiple comparison correction methods.
Zhang F, Kahali P, Suter Y, Norton I, Rigolo L, Savadjiev P, Song Y, Rathi Y, Cai W, Wells WM, Golby AJ, O’Donnell LJ. Automated connectivity-based groupwise cortical atlas generation: Application to data of neurosurgical patients with brain tumors for cortical parcellation prediction. In: Biomedical Imaging (ISBI 2017), 2017 IEEE 14th International Symposium on. IEEE; 2017 p. 774–777.
Liao R, Ning L, Chen Z, Rigolo L, Gong S, Pasternak O, Golby AJ, Rathi Y, O’Donnell LJ. Performance of unscented Kalman filter tractography in edema: Analysis of the two-tensor model. NeuroImage: Clinical 2017;15:819–831.
Norton I, Essayed WI, Zhang F, Pujol S, Yarmarkovich A, Golby AJ, Kindlmann G, Wasserman D, Johnson J, Westin C-F, O’Donnell LJ. SlicerDMRI: Open Source Diffusion MRI Software for Brain Cancer Research. Cancer Research 2017;
Zhang F, Norton I, Cai W, Song Y, Wells WM, O'Donnell LJ. Comparison between two white matter segmentation strategies: An investigation into white matter segmentation consistency. In: Biomedical Imaging (ISBI 2017), 2017 IEEE 14th International Symposium on. IEEE; 2017 p. 796–799.
Shaffer JJ, Ghayoor A, Long JD, Kim RE-Y, Lourens S, O'Donnell LJ, Westin C-F, Rathi Y, Magnotta V, Paulsen JS, others. Longitudinal diffusion changes in prodromal and early HD: Evidence of white-matter tract deterioration. Human brain mapping 2017;38(3):1460–1477.
Essayed WI, Zhang F, Unadkat P, Cosgrove RG, Golby AJ, O'Donnell LJ. White matter tractography for neurosurgical planning: A topography-based review of the current state of the art. NeuroImage: Clinical 2017;
O’Donnell LJ, Suter Y, Rigolo L, Kahali P, Zhang F, Norton I, Albi A, Olubiyi O, Meola A, Essayed WI, Unadkat P, Ciris PA, Wells WM, Rathi Y, Westin C-F, Golby AJ. Automated white matter fiber tract identification in patients with brain tumors. NeuroImage: Clinical 2017;13:138–153.
2016
Schultz T, Nedjati-Gilani G, Venkataraman A, Donnell LO, Panagiotaki E. Computational Diffusion MRI and Brain Connectivity. 2016;
Zhang F, Savadjiev P, Cai W, Song Y, Verma R, Westin C-F, O'Donnell LJ. Fiber clustering based white matter connectivity analysis for prediction of Autism Spectrum Disorder using diffusion tensor imaging. In: Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on. IEEE; 2016 p. 564–567.
Westin C-F, Knutsson H, Pasternak O, Szczepankiewicz F, Özarslan E, van Westen D, Mattisson C, Bogren M, O'Donnell LJ, Kubicki M, others. Q-space trajectory imaging for multidimensional diffusion MRI of the human brain. Neuroimage 2016;135:345–362.
Chen Z, Tie Y, Olubiyi O, Zhang F, Mehrtash A, Rigolo L, Kahali P, Norton I, Pasternak O, Rathi Y, others. Corticospinal tract modeling for neurosurgical planning by tracking through regions of peritumoral edema and crossing fibers using two-tensor unscented Kalman filter tractography. International journal of computer assisted radiology and surgery 2016;:1–12.
Zhang F, Savadjiev P, Ca{\'ı W, Song Y, Verma R, Westin C-F, O'Donnell LJ. Fiber clustering based white matter connectivity analysis for prediction of Autism Spectrum Disorder using diffusion tensor imaging. In: Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on. IEEE; 2016 p. 564–567.
Kapur T, Pieper S, Fedorov A, Fillion-Robin JC, Halle M, O'donnell L, Lasso A, Ungi T, Pinter C, Finet J, others. Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience. 2016;
Fakhri M, O’Donnell LJ, Rigolo L, Golby AJ. Mapping Eloquent Brain with Functional MRI and DTI. In: Functional Mapping of the Cerebral Cortex. Springer International Publishing; 2016 p. 41–62.
Westin C-F, Knutsson H, Pasternak O, Szczepankiewicz F, Özarslan E, van Westen D, Mattisson C, Bogren M, O'Donnell LJ, Kubicki M, others. Q-space trajectory imaging for multidimensional diffusion MRI of the human brain. NeuroImage 2016;135:345–362.
Zhang F, Savadjiev P, Ca W, Song Y, Verma R, Westin C-F, O'Donnell LJ. Fiber clustering based white matter connectivity analysis for prediction of Autism Spectrum Disorder using diffusion tensor imaging. In: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI). IEEE; 2016 p. 564–567.
Kapur T, Pieper S, Fedorov A, Fillion-Robin JC, Halle M, O'donnell L, Lasso A, Ungi T, Pinter C, Finet J, others. Increasing the Impact of Medical Image Computing Using Community-Based Open-Access Hackathons: the NA-MIC and 3D Slicer Experience. Medical Image Analysis 2016;

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