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Fully convolutional neural networks improve abdominal organ segmentation.

M. Bobo, S. Bao, Y. Huo, Y. Yao, J. Virostko, A. Plassard, I. Lyu, A. Assad, R. Abramson, M. Hilmes, and B. Landman. Medical Imaging: Image Processing, volume 10574 of SPIE Proceedings, page 105742V. SPIE, (2018)

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J Andrew Doole

Andrew J Atkins

Andrew J White

Andrew Huvos

Andrew Lee

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Deep learning for brain tumor classification.J. Paul, A. Plassard, B. Landman, and D. Fabbri. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 10137 of SPIE Proceedings, page 1013710. SPIE, (2017)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.A. Plassard, P. Kelly, A. Asman, H. Kang, M. Patel, and B. Landman. Medical Imaging: Image Processing, volume 9413 of SPIE Proceedings, page 94130K. SPIE, (2015)Technology Enablers for Big Data, Multi-Stage Analysis in Medical Image Processing.S. Bao, P. Parvathaneni, Y. Huo, Y. Barve, A. Plassard, Y. Yao, H. Sun, I. Lyu, D. Zald, B. Landman and 1 other author(s). IEEE BigData, page 1337-1346. IEEE, (2018)Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy.A. Plassard, M. McHugo, S. Heckers, and B. Landman. Medical Imaging: Image Processing, volume 10133 of SPIE Proceedings, page 101332D. SPIE, (2017)On the fallacy of quantitative segmentation for T1-weighted MRI.A. Plassard, R. Harrigan, A. Newton, S. Rane, S. Pallavaram, P. D'Haese, B. Dawant, D. Claassen, and B. Landman. Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 978416. SPIE, (2016)A Data Colocation Grid Framework for Big Data Medical Image Processing - Backend Design.S. Bao, Y. Huo, P. Parvathaneni, A. Plassard, C. Bermudez, Y. Yao, I. Lyu, A. Gokhale, and B. Landman. CoRR, (2017)Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.A. Asman, Y. Huo, A. Plassard, and B. Landman. Medical Image Anal., 26 (1): 82-91 (2015)Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson's Disease.A. Plassard. Vanderbilt University, Nashville, Tennessee, USA, (2017)base-search.net (ftvanderbilt:oai:ir.vanderbilt.edu:1803/14512).Tests of cortical parcellation based on white matter connectivity using diffusion tensor imaging.Y. Gao, K. Schilling, I. Stepniewska, A. Plassard, A. Choe, X. Li, B. Landman, and A. Anderson. NeuroImage, (2018)Toward content-based image retrieval with deep convolutional neural networks.J. Sklan, A. Plassard, D. Fabbri, and B. Landman. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 9417 of SPIE Proceedings, page 94172C. SPIE, (2015)

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Disambiguation of "Plassard, Andrew J."

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Fully convolutional neural networks improve abdominal organ segmentation.

Please choose a person to relate this publication to

J Andrew Doole

Andrew J Atkins

Andrew J White

Andrew Huvos

Andrew Lee

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Plassard, Andrew J."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Fully convolutional neural networks improve abdominal organ segmentation.

Please choose a person to relate this publication to

J Andrew Doole

Andrew J Atkins

Andrew J White

Andrew Huvos

Andrew Lee

Other publications of authors with the same name

Disambiguation

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URL
DOI
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Chicago
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Fully convolutional neural networks improve abdominal organ segmentation.