Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Seyed Raein Hashemi"'
Autor:
Seyed Raein Hashemi, Seyed Sadegh Mohseni Salehi, Deniz Erdogmus, Sanjay P. Prabhu, Simon K. Warfield, Ali Gholipour
Publikováno v:
IEEE Access, Vol 7, Pp 1721-1735 (2019)
Fully convolutional deep neural networks have been asserted to be fast and precise frameworks with great potential in image segmentation. One of the major challenges in training such networks raises when the data are unbalanced, which is common in ma
Externí odkaz:
https://doaj.org/article/8c5cacc424e24d3c9b1e166d5ec011a6
Autor:
Atul B. Shinagare, Seyed Raein Hashemi, David P. Alper, Mark M. Hammer, Giles W. Boland, Jessie L. Chai, Ramin Khorasani
Publikováno v:
Journal of the American College of Radiology. 17:1276-1284
Assess the early voluntary adoption of a certainty scale to improve communicating diagnostic certainty in radiology reports.This institutional review board-approved study was part of a multifaceted initiative to improve radiology report quality at a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b023dce0978dd73f73206311ac220b62
https://doi.org/10.1016/j.jacr.2020.03.033
https://doi.org/10.1016/j.jacr.2020.03.033
Autor:
Daniel I. Glazer, Ramin Khorasani, Atul B. Shinagare, Seyed Raein Hashemi, David P. Alper, Pamela J. DiPiro, Giles W. Boland
Publikováno v:
American Journal of Roentgenology. 214:835-842
OBJECTIVE. The objective of this study was to assess impact of a report template quality improvement (QI) initiative on use of preferred phrases for communicating normal findings in structured abdominal CT and MRI reports. SUBJECTS AND METHODS. This
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60bbdcc9654bc45b7298bc7c919dfff1
https://doi.org/10.2214/ajr.19.21735
https://doi.org/10.2214/ajr.19.21735
Publikováno v:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ISBN: 9783030466428
BrainLes@MICCAI (2)
BrainLes@MICCAI (2)
The accurate automatic segmentation of brain tumors enhances the probability of survival rate. Convolutional Neural Network (CNN) is a popular automatic approach for image evaluations. CNN provides excellent results against classical machine learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::609ec3fe2db250addd97d831d1b7c355
https://doi.org/10.1007/978-3-030-46643-5_15
https://doi.org/10.1007/978-3-030-46643-5_15
Publikováno v:
Submissions to the 2019 Kidney Tumor Segmentation Challenge: KiTS19.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9382bc1cbe5b1afca6a85f786f876be
https://doi.org/10.24926/548719.083
https://doi.org/10.24926/548719.083
Autor:
Deniz Erdogmus, Seyed Raein Hashemi, Seyed Sadegh Mohseni Salehi, Sanjay P. Prabhu, Simon K. Warfield, Ali Gholipour
Publikováno v:
IEEE Access, Vol 7, Pp 1721-1735 (2019)
Fully convolutional deep neural networks have been asserted to be fast and precise frameworks with great potential in image segmentation. One of the major challenges in training such networks raises when data is unbalanced, which is common in many me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0355a4ffb048fe5fad7a8097b1f4a176
Autor:
Ali Gholipour, Abdelhakim Ouaalam, Seyed Raein Hashemi, Simon K. Warfield, Deniz Erdogmus, Clemente Velasco-Annis, Seyed Sadegh Mohseni Salehi, Judy A. Estroff
Publikováno v:
ISBI
Brain segmentation is a fundamental first step in neuroimage analysis. In the case of fetal MRI, it is particularly challenging and important due to the arbitrary orientation of the fetus, organs that surround the fetal head, and intermittent fetal m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c4df129adecb3590dcdbf80e123ddb5
http://arxiv.org/abs/1710.09338
http://arxiv.org/abs/1710.09338