| Deep learning for brain tumor classification JS Paul, AJ Plassard, BA Landman, D Fabbri Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and …, 2017 | 232 | 2017 |
| MicroRNA signature in patients with eosinophilic esophagitis, reversibility with glucocorticoids, and assessment as disease biomarkers TX Lu, JD Sherrill, T Wen, AJ Plassard, JA Besse, JP Abonia, JP Franciosi, ... Journal of allergy and clinical immunology 129 (4), 1064-1075. e9, 2012 | 174 | 2012 |
| Learning implicit brain MRI manifolds with deep learning C Bermudez, AJ Plassard, LT Davis, AT Newton, SM Resnick, ... Medical Imaging 2018: Image Processing 10574, 408-414, 2018 | 161 | 2018 |
| Analysis and expansion of the eosinophilic esophagitis transcriptome by RNA sequencing JD Sherrill, K Kc, C Blanchard, EM Stucke, KA Kemme, MH Collins, ... Genes & Immunity 15 (6), 361-369, 2014 | 149 | 2014 |
| Consistent cortical reconstruction and multi-atlas brain segmentation Y Huo, AJ Plassard, A Carass, SM Resnick, DL Pham, JL Prince, ... NeuroImage 138, 197-210, 2016 | 125 | 2016 |
| MiR-223 deficiency increases eosinophil progenitor proliferation TX Lu, EJ Lim, JA Besse, S Itskovich, AJ Plassard, PC Fulkerson, ... The Journal of Immunology 190 (4), 1576-1582, 2013 | 89 | 2013 |
| Fully convolutional neural networks improve abdominal organ segmentation MF Bobo, S Bao, Y Huo, Y Yao, J Virostko, AJ Plassard, I Lyu, A Assad, ... Medical Imaging 2018: Image Processing 10574, 750-757, 2018 | 83 | 2018 |
| A gene expression atlas of early craniofacial development EW Brunskill, AS Potter, A Distasio, P Dexheimer, A Plassard, BJ Aronow, ... Developmental biology 391 (2), 133-146, 2014 | 74 | 2014 |
| Targeted ablation of miR-21 decreases murine eosinophil progenitor cell growth TX Lu, EJ Lim, S Itskovich, JA Besse, AJ Plassard, MK Mingler, ... PloS one 8 (3), e59397, 2013 | 66 | 2013 |
| MiR-375 is downregulated in epithelial cells after IL-13 stimulation and regulates an IL-13-induced epithelial transcriptome TX Lu, EJ Lim, T Wen, AJ Plassard, SP Hogan, LJ Martin, BJ Aronow, ... Mucosal immunology 5 (4), 388-396, 2012 | 66 | 2012 |
| Splenomegaly segmentation using global convolutional kernels and conditional generative adversarial networks Y Huo, Z Xu, S Bao, C Bermudez, AJ Plassard, J Liu, Y Yao, A Assad, ... Medical Imaging 2018: Image Processing 10574, 45-51, 2018 | 56 | 2018 |
| Toward content-based image retrieval with deep convolutional neural networks JES Sklan, AJ Plassard, D Fabbri, BA Landman Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and …, 2015 | 55 | 2015 |
| Multi-atlas learner fusion: An efficient segmentation approach for large-scale data AJ Asman, Y Huo, AJ Plassard, BA Landman Medical image analysis 26 (1), 82-91, 2015 | 51 | 2015 |
| Anatomical context improves deep learning on the brain age estimation task C Bermudez, AJ Plassard, S Chaganti, Y Huo, KS Aboud, LE Cutting, ... Magnetic Resonance Imaging 62, 70-77, 2019 | 49 | 2019 |
| Simultaneous total intracranial volume and posterior fossa volume estimation using multi‐atlas label fusion Y Huo, AJ Asman, AJ Plassard, BA Landman Human brain mapping 38 (2), 599-616, 2017 | 37 | 2017 |
| Tests of cortical parcellation based on white matter connectivity using diffusion tensor imaging Y Gao, KG Schilling, I Stepniewska, AJ Plassard, AS Choe, X Li, ... NeuroImage 170, 321-331, 2018 | 18 | 2018 |
| Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy AJ Plassard, M McHugo, S Heckers, BA Landman Medical Imaging 2017: Image Processing 10133, 666-672, 2017 | 15 | 2017 |
| Disambiguating the optic nerve from the surrounding cerebrospinal fluid: Application to MS‐related atrophy RL Harrigan, AJ Plassard, FW Bryan, G Caires, LA Mawn, LM Dethrage, ... Magnetic resonance in medicine 75 (1), 414-422, 2016 | 14 | 2016 |
| Right fronto-subcortical white matter microstructure predicts cognitive control ability on the Go/No-go task in a community sample KE Hinton, BB Lahey, V Villalta-Gil, BD Boyd, BC Yvernault, KB Werts, ... Frontiers in human neuroscience 12, 127, 2018 | 13 | 2018 |
| Theoretical and empirical comparison of big data image processing with apache hadoop and sun grid engine S Bao, FD Weitendorf, AJ Plassard, Y Huo, A Gokhale, BA Landman Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and …, 2017 | 12 | 2017 |
Bennett Allan LandmanElectrical and Computer Engineering, Vanderbilt UniversityDirección de correo verificada de vanderbilt.edu
