Susan M. Resnick
Computer Vision and Pattern Recognition · 2001–2020
A researcher in the Science corpus: 13 papers; trusts 15 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 73 citations into it; #7,669 of 21,575 by trust here, #6,954 by citations
- Radiology, Nuclear Medicine and Imaging — 54 citations into it; #580 of 3,265 by trust here, #524 by citations
- Cognitive Neuroscience — 45 citations into it; #3,812 of 10,852 by trust here, #1,539 by citations
- Psychiatry and Mental health — 43 citations into it; #190 of 1,338 by trust here, #150 by citations
- Artificial Intelligence — 24 citations into it; #33,670 of 35,345 by trust here, #18,186 by citations
- Biomedical Engineering — 14 citations into it
- Biophysics — 9 citations into it; #282 of 1,196 by trust here, #487 by citations
- Geometry and Topology — 9 citations into it
Whom Susan M. Resnick trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Christos Davatzikos
- Karl J. Friston
- John Ashburner
- Dzung L. Pham
- Leo Breiman
- Yong Fan
- Ahmet Genç
- Keith J. Worsley
- Catriona D. Good
- Andrew Holmes
Who trusts Susan M. Resnick overall
- Yong Fan
- Christos Davatzikos
- Naftali Raz
- Dinggang Shen
- Chandan Misra
- J. Best
- Daoqiang Zhang
- Nematollah Kayhan Batmanghelich
- Randy L. Buckner
- Anders M. Fjell
Papers from Susan M. Resnick's perspective
Ordered by how strongly the researchers Susan M. Resnick trusts endorse each paper. Same corpus, a different order for every researcher.
- Voxel-based morphometry--the methods.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Densely Connected Convolutional Networks
- Dropout: a simple way to prevent neural networks from overfitting
- Statistical parametric maps in functional imaging: A general linear approach
- Visualizing and Understanding Convolutional Networks
- Statistical learning theory
- HAMMER: hierarchical attribute matching mechanism for elastic registration (IEEE Transactions on Medical Imaging)
- An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest (NeuroImage)
Their papers
- MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide. (2020) — 356 citations
- 3D Whole Brain Segmentation using Spatially Localized Atlas Network Tiles (2019) — 296 citations
- Learning Implicit Brain MRI Manifolds with Deep Learning (2018) — 139 citations
- MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection (2015) — 317 citations
- Association of Hearing Impairment with Brain Volume Changes in Older Adults (2014) — 491 citations
- Hearing Loss and Cognition in the Baltimore Longitudinal Study of Aging (2011) — 650 citations
- Hearing Loss and Incident Dementia (2011) — 1,494 citations
- Longitudinal Changes in Cortical Thickness Associated with Normal Aging (2010) — 341 citations
- Detection of prodromal Alzheimer's disease via pattern classification of magnetic resonance imaging. (2008) — 403 citations
- Structural and functional biomarkers of prodromal Alzheimer's disease: A high-dimensional pattern classification study (2008) — 317 citations
- Morphological classification of brains via high-dimensional shape transformations and machine learning methods (2004) — 355 citations
- Longitudinal Magnetic Resonance Imaging Studies of Older Adults: A Shrinking Brain (2003) — 1,405 citations
- Voxel-Based Morphometry Using the RAVENS Maps: Methods and Validation Using Simulated Longitudinal Atrophy (2001) — 464 citations