Radiology Personnel
David Haynor, M.D., Ph.D.
Professor
Neuroradiology
Biography
Dr. Haynor is a neuroradiologist with a longstanding interest in image processing and computer applications in radiology.
Awards and Honors
- National Science Foundation Grant, August 08, 2017
Recent Publications (via Semantic Scholar)
L. Gold, R. Cody, W. K. Tan, et al. - Published 2022 - OSTEOPOROSIS INTERNATIONAL
The BRAIN Initiative Cell Census Network Data Ecosystem: A User’s Guide
M. Hawrylycz, M. Martone, P. Hof, et al. - Published 2022 - BIORXIV
Finding atrophy patterns of grey matter through orthonormal non-negative factorization
Wenbo Zhang, Kwun Chuen Gary Chan, D. Shibata, et al. - Published 2021 - MEDICAL IMAGING
Radiogenomic modeling predicts survival-associated prognostic groups in glioblastoma
Nicholas Nuechterlein, B. Li, A. Feroze, et al. - Published 2021 - NEURO-ONCOLOGY ADVANCES
Learning Cortical Parcellations Using Graph Neural Networks
K. Eschenburg, T. Grabowski, D. Haynor - Published 2021 - FRONTIERS IN NEUROSCIENCE
Applying Artificial Intelligence to Mitigate Effects of Patient Motion or Other Complicating Factors on Image Quality.
X. V. Nguyen, M. A. Oztek, Devi D Nelakurti, et al. - Published 2020 - TOPICS IN MAGNETIC RESONANCE IMAGING : TMRI
Making Magnets More Attractive utions to Patient Comfort in MRI Physics and Engineering Contrib
C. Brunnquell, M. Hoff, N. Balu, et al. - Published 2020
Making Magnets More Attractive: Physics and Engineering Contributions to Patient Comfort in MRI.
C. Brunnquell, M. Hoff, N. Balu, et al. - Published 2020 - TOPICS IN MAGNETIC RESONANCE IMAGING : TMRI
DicomAnnotator: a Configurable Open-Source Software Program for Efficient DICOM Image Annotation
Qifei Dong, Gang Luo, D. Haynor, et al. - Published 2020 - JOURNAL OF DIGITAL IMAGING
NIMG-46. RADIOGENOMIC FEATURES PREDICT CLINICALLY RELEVANT GENOME-WIDE ALTERATION SIGNATURES IN GLIOBLASTOMA
Nicholas Nuechterlein, B. Li, J. Fink, et al. - Published 2020