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

Y. Huo, Z. Xu, S. Bao, C. Bermudez, A. Plassard, J. Liu, Y. Yao, A. Assad, R. Abramson, and B. Landman. Medical Imaging: Image Processing, volume 10574 of SPIE Proceedings, page 1057409. SPIE, (2018)

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Aron Abramson

Max Abramson

Giuseppe G G Manzardo

G Lüers

G Baumann

Other publications of authors with the same name

Validation and optimization of multi-organ segmentation on clinical imaging archives.O. Tang, Y. Xu, Y. Tang, H. Lee, Y. Chen, D. Gao, S. Han, R. Gao, M. Savona, R. Abramson and 2 other author(s). Medical Imaging: Image Processing, volume 11313 of SPIE Proceedings, page 113132O. SPIE, (2020)Splenomegaly Segmentation on Multi-Modal MRI Using Deep Convolutional Networks.Y. Huo, Z. Xu, S. Bao, C. Bermudez, H. Moon, P. Parvathaneni, T. Moyo, M. Savona, A. Assad, R. Abramson and 1 other author(s). IEEE Trans. Medical Imaging, 38 (5): 1185-1196 (2019)RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior.H. Lee, Y. Tang, S. Bao, R. Abramson, Y. Huo, and B. Landman. CoRR, (2020)SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth.Y. Huo, Z. Xu, H. Moon, S. Bao, A. Assad, T. Moyo, M. Savona, R. Abramson, and B. Landman. CoRR, (2018)Multi-atlas segmentation enables robust multi-contrast MRI spleen segmentation for splenomegaly.Y. Huo, J. Liu, Z. Xu, R. Harrigan, A. Assad, R. Abramson, and B. Landman. Medical Imaging: Image Processing, volume 10133 of SPIE Proceedings, page 101330A. SPIE, (2017)Whole abdominal wall segmentation using Augmented Active Shape Models (AASM) with multi-atlas label fusion and level set.Z. Xu, R. Baucom, R. Abramson, B. Poulose, and B. Landman. Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 97840U. SPIE, (2016)Robust Multicontrast MRI Spleen Segmentation for Splenomegaly Using Multi-Atlas Segmentation.Y. Huo, J. Liu, Z. Xu, R. Harrigan, A. Assad, R. Abramson, and B. Landman. IEEE Trans. Biomed. Eng., 65 (2): 336-343 (2018)Adversarial synthesis learning enables segmentation without target modality ground truth.Y. Huo, Z. Xu, S. Bao, A. Assad, R. Abramson, and B. Landman. ISBI, page 1217-1220. IEEE, (2018)Splenomegaly segmentation using global convolutional kernels and conditional generative adversarial networks.Y. Huo, Z. Xu, S. Bao, C. Bermudez, A. Plassard, J. Liu, Y. Yao, A. Assad, R. Abramson, and B. Landman. Medical Imaging: Image Processing, volume 10574 of SPIE Proceedings, page 1057409. SPIE, (2018)Multi-atlas segmentation for abdominal organs with Gaussian mixture models.R. Burke, Z. Xu, C. Lee, R. Baucom, B. Poulose, R. Abramson, and B. Landman. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 9417 of SPIE Proceedings, page 941707. SPIE, (2015)

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Disambiguation of "Abramson, Richard G."

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

Please choose a person to relate this publication to

Aron Abramson

Max Abramson

Giuseppe G G Manzardo

G Lüers

G Baumann

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Abramson, Richard G."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Splenomegaly segmentation using global convolutional kernels and conditional generative adversarial networks.

Please choose a person to relate this publication to

Aron Abramson

Max Abramson

Giuseppe G G Manzardo

G Lüers

G Baumann

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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Splenomegaly segmentation using global convolutional kernels and conditional generative adversarial networks.