Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Zhoubing Xu"'
Autor:
Sebastian Marschner, Manasi Datarb, Aurélie Gaasch, Zhoubing Xu, Sasa Grbic, Guillaume Chabin, Bernhard Geiger, Julian Rosenman, Stefanie Corradini, Maximilian Niyazi, Tobias Heimann, Christian Möhler, Fernando Vega, Claus Belka, Christian Thieke
Publikováno v:
Radiation Oncology, Vol 17, Iss 1, Pp 1-9 (2022)
Abstract Background We describe and evaluate a deep network algorithm which automatically contours organs at risk in the thorax and pelvis on computed tomography (CT) images for radiation treatment planning. Methods The algorithm identifies the regio
Externí odkaz:
https://doaj.org/article/62ada65283ab4ac78333d93e796bb5ce
Autor:
Sebastian Marschner, Manasi Datar, Aurélie Gaasch, Zhoubing Xu, Sasa Grbic, Guillaume Chabin, Bernhard Geiger, Julian Rosenman, Stefanie Corradini, Maximilian Niyazi, Tobias Heimann, Christian Möhler, Fernando Vega, Claus Belka, Christian Thieke
Publikováno v:
Radiation Oncology, Vol 17, Iss 1, Pp 1-1 (2022)
Externí odkaz:
https://doaj.org/article/82bd818104d24478a5bb618c02fe21c8
Autor:
Zhoubing Xu, Andrew J Asman, Rebeccah B Baucom, Richard G Abramson, Benjamin K Poulose, Bennett A Landman
Publikováno v:
PLoS ONE, Vol 10, Iss 10, p e0141671 (2015)
We described and validated a quantitative anatomical labeling protocol for extracting clinically relevant quantitative parameters for ventral hernias (VH) from routine computed tomography (CT) scans. This information was then used to predict the need
Externí odkaz:
https://doaj.org/article/5821e3a81aa749b39d3849232b311abd
Autor:
Zhoubing Xu, Shunxing Bao, Yuankai Huo, Michael R. Savona, Hyeonsoo Moon, Richard G. Abramson, Tamara K. Moyo, Albert Assad, Bennett A. Landman
Publikováno v:
IEEE Transactions on Medical Imaging. 38:1016-1025
A key limitation of deep convolutional neural networks (DCNN) based image segmentation methods is the lack of generalizability. Manually traced training images are typically required when segmenting organs in a new imaging modality or from distinct d
Autor:
Riqiang Gao, Bennett A. Landman, Yuankai Huo, Yucheng Tang, Jeffery M. Spraggins, Shunxing Bao, Agnes B. Fogo, Brent Savoie, Raymond C. Harris, Ho Hin Lee, Mark P. de Caestecker, Zhoubing Xu
Publikováno v:
Proc SPIE Int Soc Opt Eng
Renal segmentation on contrast-enhanced computed tomography (CT) provides distinct spatial context and morphology. Current studies for renal segmentations are highly dependent on manual efforts, which are time-consuming and tedious. Hence, developing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b260f9a09d65cf7dc4719a5e3f3b8d83
https://europepmc.org/articles/PMC8442958/
https://europepmc.org/articles/PMC8442958/
Autor:
Yucheng Tang, Xin Yu, Jeffrey M. Spraggins, Riqiang Gao, Bennett A. Landman, Shunxing Bao, Yuyin Zhou, Zhoubing Xu, Yuankai Huo, John Virostko, Ho Hin Lee, Qi Yang
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030871925
MICCAI (1)
MICCAI (1)
Pancreas CT segmentation offers promise at understanding the structural manifestation of metabolic conditions. To date, the medical primary record of conditions that impact the pancreas is in the electronic health record (EHR) in terms of diagnostic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3528e8e1e178e824360d7497f2cd1d96
https://doi.org/10.1007/978-3-030-87193-2_3
https://doi.org/10.1007/978-3-030-87193-2_3
Autor:
S. Kevin Zhou, Zhoubing Xu
Publikováno v:
Handbook of Medical Image Computing and Computer Assisted Intervention ISBN: 9780128161760
In this chapter we present discriminative learning approaches for landmark detection and shape segmentation. Specifically, we elaborate different landmark representations and demonstrate how to use them in different supervised learning methods. We th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d97b450326e43a00c0000951c8328c73
https://doi.org/10.1016/b978-0-12-816176-0.00014-4
https://doi.org/10.1016/b978-0-12-816176-0.00014-4
Autor:
Guillaume Chabin, Vijay Shah, Sasa Grbic, Michael Schäfers, Robert Seifert, Ken Herrmann, Jens Kleesiek, Zhoubing Xu, Bruce S Spottiswoode, Kambiz Rahbar
Prostate specific membrane antigen (PSMA) targeting Positron Emission Tomography (PET) imaging is becoming the reference standard for prostate cancer (PC) staging, especially in advanced disease. Yet, the implications of PSMA-PET derived whole-body t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d54b07a8964545fa94c38bba736fbda
https://www.ncbi.nlm.nih.gov/pubmed/32332147
https://www.ncbi.nlm.nih.gov/pubmed/32332147
Autor:
Richard G. Abramson, Albert Assad, Yuankai Huo, Zhoubing Xu, Jiaqi Liu, Bennett A. Landman, Robert L. Harrigan
Publikováno v:
IEEE Transactions on Biomedical Engineering. 65:336-343
Objective: Magnetic resonance imaging (MRI) is an essential imaging modality in noninvasive splenomegaly diagnosis. However, it is challenging to achieve spleen volume measurement from three-dimensional MRI given the diverse structural variations of
Autor:
Prasanna Parvathaneni, Zhoubing Xu, Camilo Bermudez, Laurie E. Cutting, Susan M. Resnick, Yunxi Xiong, Shunxing Bao, Bennett A. Landman, Katherine S. Aboud, Yuankai Huo
Publikováno v:
Neuroimage
Detailed whole brain segmentation is an essential quantitative technique in medical image analysis, which provides a non-invasive way of measuring brain regions from a clinical acquired structural magnetic resonance imaging (MRI). Recently, deep conv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2cfb00c6d43e9bf585a0a5fb47b1e35
https://europepmc.org/articles/PMC6536356/
https://europepmc.org/articles/PMC6536356/