People


Daniel Tward
  
Daniel J. Tward
• Assistant Professor - Neurology
• Assistant Professor - Computational Medicine
635 Charles E. Young Dr. South
Suite 225
Los Angeles, CA 90095

Biography

Dr. Daniel Tward’s research uses imaging data to understand how disease affects the brain’s structure. He develops and applies computational tools that overcome challenges in neuroimaging, such as the wide range of imaging technologies producing data, and the complex geometry of the brain’s anatomy. One focus involves studying neurodegeneration of the medial temporal lobe in early Alzheimer’s disease, connecting information available in clinical MRI with microscopy data observed at autopsy.

Dr. Tward obtained his bachelor’s degree in physics and physiology from the University of Toronto, his PhD in biomedical engineering from Johns Hopkins University, and completed postdoctoral training in biomedical engineering and neuropathology at the Kavli Neuroscience Discovery Institute. He holds a joint appointment in the Department of Neurology as part of the Ahmanson-Lovelace Brain Mapping Center, and in the Department of Computational Medicine.

Publications

Diffeomorphic Registration With Intensity Transformation and Missing Data: Application to 3D Digital Pathology of Alzheimer's Disease.
Tward D; Brown T; Kageyama Y; Patel J; Hou Z; Mori S; Albert M; Troncoso J; Miller M;
Frontiers in neuroscience. 2020-Dec;14(52)
PMID: 32116503    DOI: 10.3389/fnins.2020.00052   
Diffeomorphic Upsampling of Serially Acquired Sparse 2D Cross-Sections in Cardiac MRI.
Lee BC; Tward DJ; Wei J; Tipre D; Weiss RG; Miller MI; Ardekani S;
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference. 2019-Jul;2019(4491-4495)
PMID: 31946863    DOI: 10.1109/EMBC.2019.8856317   
Cortical thickness atrophy in the transentorhinal cortex in mild cognitive impairment.
Kulason S; Tward DJ; Brown T; Sicat CS; Liu CF; Ratnanather JT; Younes L; Bakker A; Gallagher M; Albert M; Miller MI; Alzheimer's Disease Neuroimaging Initiative;
NeuroImage. Clinical. 2019-Dec;21(101617)
PMID: 30552075    DOI: 10.1016/j.nicl.2018.101617   
ESTIMATING DIFFEOMORPHIC MAPPINGS BETWEEN TEMPLATES AND NOISY DATA: VARIANCE BOUNDS ON THE ESTIMATED CANONICAL VOLUME FORM.
Tward DJ; Mitra PP; Miller MI;
Quarterly of applied mathematics. 2019-Dec;77(467-488)
PMID: 31866695    DOI: 10.1090/qam/1527   
On variational solutions for whole brain serial-section histology using a Sobolev prior in the computational anatomy random orbit model.
Lee BC; Tward DJ; Mitra PP; Miller MI;
PLoS computational biology. 2018-Dec;14(e1006610):12
PMID: 30586384    DOI: 10.1371/journal.pcbi.1006610   
A community-developed open-source computational ecosystem for big neuro data.
Vogelstein JT; Perlman E; Falk B; Baden A; Gray Roncal W; Chandrashekhar V; Collman F; Seshamani S; Patsolic JL; Lillaney K; Kazhdan M; Hider R; Pryor D; Matelsky J; Gion T; Manavalan P; Wester B; Chevillet M; Trautman ET; Khairy K; Bridgeford E; Kleissas DM; Tward DJ; Crow AK; Hsueh B; Wright MA; Miller MI; Smith SJ; Vogelstein RJ; Deisseroth K; Burns R;
Nature methods. 2018-Dec;15(846-847):11
PMID: 30377345    DOI: 10.1038/s41592-018-0181-1   
Computational anatomy and diffeomorphometry: A dynamical systems model of neuroanatomy in the soft condensed matter continuum.
Miller MI; Arguillère S; Tward DJ; Younes L;
Wiley interdisciplinary reviews. Systems biology and medicine. 2018-Dec;10(e1425):6
PMID: 29862670    DOI: 10.1002/wsbm.1425   
On the Complexity of Human Neuroanatomy at the Millimeter Morphome Scale: Developing Codes and Characterizing Entropy Indexed to Spatial Scale.
Tward DJ; Miller MI;
Frontiers in neuroscience. 2017-Dec;11(577)
PMID: 29093658    DOI: 10.3389/fnins.2017.00577   
Entorhinal and transentorhinal atrophy in mild cognitive impairment using longitudinal diffeomorphometry.
Tward DJ; Sicat CS; Brown T; Bakker A; Gallagher M; Albert M; Miller M;
Alzheimer's & dementia (Amsterdam, Netherlands). 2017-Dec;9(41-50)
PMID: 28971142    DOI: 10.1016/j.dadm.2017.07.005   
Parametric Surface Diffeomorphometry for Low Dimensional Embeddings of Dense Segmentations and Imagery.
Tward D; Miller M; Trouve A; Younes L;
IEEE transactions on pattern analysis and machine intelligence. 2017-Dec;39(1195-1208):6
PMID: 27295651    DOI: 10.1109/TPAMI.2016.2578317   
Linking white matter and deep gray matter alterations in premanifest Huntington disease.
Faria AV; Ratnanather JT; Tward DJ; Lee DS; van den Noort F; Wu D; Brown T; Johnson H; Paulsen JS; Ross CA; Younes L; Miller MI; PREDICT-HD Investigators and Coordinators of the Huntington Study Group;
NeuroImage. Clinical. 2016-Dec;11(450-460)
PMID: 27104139    DOI: 10.1016/j.nicl.2016.02.014   
The development of a population of 4D pediatric XCAT phantoms for imaging research and optimization.
Segars WP; Norris H; Sturgeon GM; Zhang Y; Bond J; Minhas A; Tward DJ; Ratnanather JT; Miller MI; Frush D; Samei E;
Medical physics. 2015-Aug;42(4719-26):8
PMID: 26233199    DOI: 10.1118/1.4926847   
Morphometry of the amygdala in schizophrenia and psychotic bipolar disorder.
Mahon PB; Lee DS; Trinh H; Tward D; Miller MI; Younes L; Barta PE; Ratnanather JT;
Schizophrenia research. 2015-May;164(199-202):1-3
PMID: 25766598    DOI: 10.1016/j.schres.2015.02.011   
Amygdalar atrophy in symptomatic Alzheimer's disease based on diffeomorphometry: the BIOCARD cohort.
Miller MI; Younes L; Ratnanather JT; Brown T; Trinh H; Lee DS; Tward D; Mahon PB; Mori S; Albert M; BIOCARD Research Team;
Neurobiology of aging. 2015-Jan;36 Suppl 1(S3-S10)
PMID: 25444602    DOI: 10.1016/j.neurobiolaging.2014.06.032   
Network Neurodegeneration in Alzheimer's Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing.
Miller MI; Ratnanather JT; Tward DJ; Brown T; Lee DS; Ketcha M; Mori K; Wang MC; Mori S; Albert MS; Younes L; BIOCARD Research Team;
Frontiers in bioengineering and biotechnology. 2015-Dec;3(54)
PMID: 26284236    DOI: 10.3389/fbioe.2015.00054   
A set of 4D pediatric XCAT reference phantoms for multimodality research.
Norris H; Zhang Y; Bond J; Sturgeon GM; Minhas A; Tward DJ; Ratnanather JT; Miller MI; Frush D; Samei E; Segars WP;
Medical physics. 2014-Mar;41(033701):3
PMID: 24593745    DOI: 10.1118/1.4864238   
Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization.
Segars WP; Bond J; Frush J; Hon S; Eckersley C; Williams CH; Feng J; Tward DJ; Ratnanather JT; Miller MI; Frush D; Samei E;
Medical physics. 2013-Apr;40(043701):4
PMID: 23556927    DOI: 10.1118/1.4794178   
Robust Diffeomorphic Mapping via Geodesically Controlled Active Shapes.
Tward DJ; Ma J; Miller MI; Younes L;
International journal of biomedical imaging. 2013-Dec;2013(205494)
PMID: 23690757    DOI: 10.1155/2013/205494   
Effects of protocol and obesity on dose conversion factors in adult body CT.
Li X; Samei E; Williams CH; Segars WP; Tward DJ; Miller MI; Ratnanather JT; Paulson EK; Frush DP;
Medical physics. 2012-Nov;39(6550-71):11
PMID: 23127050    DOI: 10.1118/1.4754584   
Beyond noise power in 3D computed tomography: the local NPS and off-diagonal elements of the Fourier domain covariance matrix.
Pineda AR; Tward DJ; Gonzalez A; Siewerdsen JH;
Medical physics. 2012-Jun;39(3240-52):6
PMID: 22755707    DOI: 10.1118/1.4705354   
Analysis of Fourier-domain task-based detectability index in tomosynthesis and cone-beam CT in relation to human observer performance.
Gang GJ; Lee J; Stayman JW; Tward DJ; Zbijewski W; Prince JL; Siewerdsen JH;
Medical physics. 2011-Apr;38(1754-68):4
PMID: 21626910    DOI: 10.1118/1.3560428   
Patient Specific Dosimetry Phantoms Using Multichannel LDDMM of the Whole Body.
Tward DJ; Ceritoglu C; Kolasny A; Sturgeon GM; Segars WP; Miller MI; Ratnanather JT;
International journal of biomedical imaging. 2011-Dec;2011(481064)
PMID: 21960989    DOI: 10.1155/2011/481064   
Anatomical background and generalized detectability in tomosynthesis and cone-beam CT.
Gang GJ; Tward DJ; Lee J; Siewerdsen JH;
Medical physics. 2010-May;37(1948-65):5
PMID: 20527529    DOI: 10.1118/1.3352586   
The Generalized NEQ and Detectability Index for Tomosynthesis and Cone-Beam CT: From Cascaded Systems Analysis to Human Observers.
Gang GJ; Lee J; Stayman JW; Tward DJ; Zbijewski W; Prince JL; Siewerdsen JH;
Proceedings of SPIE--the International Society for Optical Engineering. 2010-Mar-22;7622
PMID: 24307930    DOI: 10.1117/12.845462   
Noise aliasing and the 3D NEQ of flat-panel cone-beam CT: effect of 2D/3D apertures and sampling.
Tward DJ; Siewerdsen JH;
Medical physics. 2009-Aug;36(3830-43):8
PMID: 19746816    DOI: 10.1118/1.3166933   
Cascaded systems analysis of the 3D noise transfer characteristics of flat-panel cone-beam CT.
Tward DJ; Siewerdsen JH;
Medical physics. 2008-Dec;35(5510-29):12
PMID: 19175110    DOI: 10.1118/1.3002414   
Soft-tissue detectability in cone-beam CT: evaluation by 2AFC tests in relation to physical performance metrics.
Tward DJ; Siewerdsen JH; Daly MJ; Richard S; Moseley DJ; Jaffray DA; Paul NS;
Medical physics. 2007-Nov;34(4459-71):11
PMID: 18072510    DOI: 10.1118/1.2790586   
Optimal kvp selection for dual-energy imaging of the chest: evaluation by task-specific observer preference tests.
Williams DB; Siewerdsen JH; Tward DJ; Paul NS; Dhanantwari AC; Shkumat NA; Richard S; Yorkston J; Van Metter R;
Medical physics. 2007-Oct;34(3916-25):10
PMID: 17985637    DOI: 10.1118/1.2776239