Andrew J. Plassard

According to our database, Andrew J. Plassard authored at least 22 papers between 2015 and 2019.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2019

Deep Learning Captures More Accurate Diffusion Fiber Orientations Distributions than Constrained Spherical Deconvolution.

Vishwesh Nath, Kurt G. Schilling, Colin B. Hansen, Prasanna Parvathaneni, Allison E. Hainline, Camilo Bermudez, Andrew J. Plassard, Vaibhav A. Janve, Yurui Gao, Justin A. Blaber, Iwona Stepniewska, Adam W. Anderson, Bennett A. Landman

CoRR, 2019

2018

Tests of cortical parcellation based on white matter connectivity using diffusion tensor imaging.

Yurui Gao, Kurt G. Schilling, Iwona Stepniewska, Andrew J. Plassard, Ann S. Choe, Xia Li, Bennett A. Landman, Adam W. Anderson

NeuroImage, 2018

Splenomegaly segmentation using global convolutional kernels and conditional generative adversarial networks.

Yuankai Huo, Zhoubing Xu, Shunxing Bao, Camilo Bermudez, Andrew J. Plassard, Jiaqi Liu, Yuang Yao, Albert Assad, Richard G. Abramson, Bennett A. Landman

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Fully convolutional neural networks improve abdominal organ segmentation.

Meg F. Bobo, Shunxing Bao, Yuankai Huo, Yuang Yao, Jack Virostko, Andrew J. Plassard, Ilwoo Lyu, Albert Assad, Richard G. Abramson, Melissa A. Hilmes, Bennett A. Landman

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Learning implicit brain MRI manifolds with deep learning.

Camilo Bermudez, Andrew J. Plassard, Larry T. Davis, Allen T. Newton, Susan M. Resnick, Bennett A. Landman

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Technology Enablers for Big Data, Multi-Stage Analysis in Medical Image Processing.

Shunxing Bao, Prasanna Parvathaneni, Yuankai Huo, Yogesh D. Barve, Andrew J. Plassard, Yuang Yao, Hongyang Sun, Ilwoo Lyu, David H. Zald, Bennett A. Landman, Aniruddha S. Gokhale

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson's Disease.

Andrew J. Plassard

PhD thesis, 2017

A Data Colocation Grid Framework for Big Data Medical Image Processing - Backend Design.

Shunxing Bao, Yuankai Huo, Prasanna Parvathaneni, Andrew J. Plassard, Camilo Bermudez, Yuang Yao, Ilwoo Lyu, Aniruddha S. Gokhale, Bennett A. Landman

CoRR, 2017

Structural-functional relationships between eye orbital imaging biomarkers and clinical visual assessments.

Xiuya Yao, Shikha Chaganti, Kunal P. Nabar, Katrina Nelson, Andrew J. Plassard, Robert L. Harrigan, Louise A. Mawn, Bennett A. Landman

Proceedings of the Medical Imaging 2017: Image Processing, 2017

Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy.

Andrew J. Plassard, Maureen McHugo, Stephan Heckers, Bennett A. Landman

Proceedings of the Medical Imaging 2017: Image Processing, 2017

Multi-modal and targeted imaging improves automated mid-brain segmentation.

Andrew J. Plassard, Pierre-François D'Haese, Srivatsan Pallavaram, Allen T. Newton, Daniel O. Claassen, Benoit M. Dawant, Bennett A. Landman

Proceedings of the Medical Imaging 2017: Image Processing, 2017

Deep learning for brain tumor classification.

Justin S. Paul, Andrew J. Plassard, Bennett A. Landman, Daniel Fabbri

Proceedings of the Medical Imaging 2017: Biomedical Applications in Molecular, 2017

Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service.

Shunxing Bao, Andrew J. Plassard, Bennett A. Landman, Aniruddha S. Gokhale

Proceedings of the 2017 IEEE International Conference on Cloud Engineering, 2017

2016

Consistent cortical reconstruction and multi-atlas brain segmentation.

Yuankai Huo, Andrew J. Plassard, Aaron Carass, Susan M. Resnick, Dzung L. Pham, Jerry L. Prince, Bennett A. Landman

NeuroImage, 2016

Improving cerebellar segmentation with statistical fusion.

Andrew J. Plassard, Zhen Yang, Jerry L. Prince, Daniel O. Claassen, Bennett A. Landman

Proceedings of the Medical Imaging 2016: Image Processing, 2016

On the fallacy of quantitative segmentation for T1-weighted MRI.

Andrew J. Plassard, Robert L. Harrigan, Allen T. Newton, Swati D. Rane, Srivatsan Pallavaram, Pierre-François D'Haese, Benoit M. Dawant, Daniel O. Claassen, Bennett A. Landman

Proceedings of the Medical Imaging 2016: Image Processing, 2016

A Bayesian framework for early risk prediction in traumatic brain injury.

Shikha Chaganti, Andrew J. Plassard, Laura Wilson, Miya A. Smith, Mayur B. Patel, Bennett A. Landman

Proceedings of the Medical Imaging 2016: Image Processing, 2016

2015

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

Andrew J. Asman, Yuankai Huo, Andrew J. Plassard, Bennett A. Landman

Medical Image Anal., 2015

Revealing latent value of clinically acquired CTs of traumatic brain injury through multi-atlas segmentation in a retrospective study of 1, 003 with external cross-validation.

Andrew J. Plassard, Patrick D. Kelly, Andrew J. Asman, Hakmook Kang, Mayur B. Patel, Bennett A. Landman

Proceedings of the Medical Imaging 2015: Image Processing, 2015

Bootstrapping white matter segmentation, Eve++.

Andrew J. Plassard, Kendra E. Hinton, Vijay K. Venkatraman, Christopher E. Gonzalez, Susan M. Resnick, Bennett A. Landman

Proceedings of the Medical Imaging 2015: Image Processing, 2015

Constructing a statistical atlas of the radii of the optic nerve and cerebrospinal fluid sheath in young healthy adults.

Robert L. Harrigan, Andrew J. Plassard, Louise A. Mawn, Robert L. Galloway, Seth A. Smith, Bennett A. Landman

Proceedings of the Medical Imaging 2015: Image Processing, 2015

Toward content-based image retrieval with deep convolutional neural networks.

Judah E. S. Sklan, Andrew J. Plassard, Daniel Fabbri, Bennett A. Landman

Proceedings of the Medical Imaging 2015: Biomedical Applications in Molecular, 2015