Andrew Beers
Andrew Beers
University of Washington
Verified email at - Homepage
TitleCited byYear
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks
JM Brown, JP Campbell, A Beers, K Chang, S Ostmo, RVP Chan, J Dy, ...
JAMA ophthalmology 136 (7), 803-810, 2018
Residual convolutional neural network for the determination of IDH status in low-and high-grade gliomas from MR imaging
K Chang, HX Bai, H Zhou, C Su, WL Bi, E Agbodza, VK Kavouridis, ...
Clinical Cancer Research 24 (5), 1073-1081, 2018
Distributed deep learning networks among institutions for medical imaging
K Chang, N Balachandar, C Lam, D Yi, J Brown, A Beers, B Rosen, ...
Journal of the American Medical Informatics Association 25 (8), 945-954, 2018
Temporo-Spatial Collaborative Filtering for Parameter Estimation in Noisy DCE-MRI Sequences: Application to Breast Cancer Chemotherapy Response
X Zhu, D Sengupta, A Beers, KC Jayashree, TL Willke
arXiv preprint arXiv:1803.01099, 2018
ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI
S Winzeck, A Hakim, R McKinley, JA Pinto, V Alves, C Silva, M Pisov, ...
Frontiers in neurology 9, 2018
Sequential 3D U-Nets for biologically-informed brain tumor segmentation
A Beers, K Chang, J Brown, E Sartor, CP Mammen, E Gerstner, B Rosen, ...
arXiv preprint arXiv:1709.02967, 2017
High-resolution medical image synthesis using progressively grown generative adversarial networks
A Beers, J Brown, K Chang, JP Campbell, S Ostmo, MF Chiang, ...
arXiv preprint arXiv:1805.03144, 2018
Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning
JM Brown, JP Campbell, A Beers, K Chang, K Donohue, S Ostmo, ...
Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and …, 2018
A multi-institutional comparison of dynamic contrast-enhanced magnetic resonance imaging parameter calculations
J Head, NRMRID Cooperative
Scientific reports 7, 2017
Semi‐automated pulmonary nodule interval segmentation using the NLST data
Y Balagurunathan, A Beers, J Kalpathy‐Cramer, M McNitt‐Gray, ...
Medical physics 45 (3), 1093-1107, 2018
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
B Lecouat, K Chang, CS Foo, B Unnikrishnan, JM Brown, H Zenati, ...
arXiv preprint arXiv:1812.07832, 2018
DeepNeuro: an open-source deep learning toolbox for neuroimaging
A Beers, J Brown, K Chang, K Hoebel, E Gerstner, B Rosen, ...
arXiv preprint arXiv:1808.04589, 2018
Automated fundus image quality assessment in retinopathy of prematurity using deep convolutional neural networks
AS Coyner, R Swan, JP Campbell, S Ostmo, JM Brown, ...
Ophthalmology Retina 3 (5), 444-450, 2019
Making sense of large data sets without annotations: analyzing age-related correlations from lung CT scans
YD Cid, A Mamonov, A Beers, A Thomas, V Kovalev, J Kalpathy-Cramer, ...
Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and …, 2017
Automatic assessment of glioma burden: A deep learning algorithm for fully automated volumetric and bi-dimensional measurement
K Chang, AL Beers, HX Bai, JM Brown, KI Ly, X Li, JT Senders, ...
Neuro-oncology, 2019
Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference …
LC Bell, N Semmineh, H An, C Eldeniz, R Wahl, KM Schmainda, MA Prah, ...
Tomography 5 (1), 110, 2019
Bevacizumab reduces permeability and concurrent temozolomide delivery in a subset of patients with recurrent glioblastoma
E Gerstner, KE Emblem, K Chang, B Vakulenko-Lagun, YF Yen, AL Beers, ...
Clinical Cancer Research, clincanres. 1739.2019, 2019
Resources and datasets for radiomics
K Chang, A Beers, J Brown, J Kalpathy-Cramer
Radiomics and Radiogenomics: Technical Basis and Clinical Applications, 179, 2019
Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture
MA Silva, J Patel, V Kavouridis, T Gallerani, A Beers, K Chang, KV Hoebel, ...
World neurosurgery, 2019
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