Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Daniel Khapun"'
Autor:
Yoel Shoshan, Ran Bakalo, Flora Gilboa-Solomon, Vadim Ratner, Ella Barkan, Michal Ozery-Flato, Mika Amit, Daniel Khapun, Emily B. Ambinder, Eniola T. Oluyemi, Babita Panigrahi, Philip A. DiCarlo, Michal Rosen-Zvi, Lisa A. Mullen
Publikováno v:
Radiology. 303:69-77
Background Digital breast tomosynthesis (DBT) has higher diagnostic accuracy than digital mammography, but interpretation time is substantially longer. Artificial intelligence (AI) could improve reading efficiency. Purpose To evaluate the use of AI t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f78280815d2cb0a42886763e65b37eaf
https://doi.org/10.1148/radiol.211105
https://doi.org/10.1148/radiol.211105
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030983840
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::274985da047a6473e5e59cf4a2ebb7ae
https://doi.org/10.1007/978-3-030-98385-7_14
https://doi.org/10.1007/978-3-030-98385-7_14
Autor:
Nicholas Konz, Mateusz Buda, Hanxue Gu, Ashirbani Saha, Jichen Yang, Jakub Chłędowski, Jungkyu Park, Jan Witowski, Krzysztof J. Geras, Yoel Shoshan, Flora Gilboa-Solomon, Daniel Khapun, Vadim Ratner, Ella Barkan, Michal Ozery-Flato, Robert Martí, Akinyinka Omigbodun, Chrysostomos Marasinou, Noor Nakhaei, William Hsu, Pranjal Sahu, Md Belayat Hossain, Juhun Lee, Carlos Santos, Artur Przelaskowski, Jayashree Kalpathy-Cramer, Benjamin Bearce, Kenny Cha, Keyvan Farahani, Nicholas Petrick, Lubomir Hadjiiski, Karen Drukker, Samuel G. Armato, Maciej A. Mazurowski
Publikováno v:
JAMA Network Open. 6:e230524
ImportanceAn accurate and robust artificial intelligence (AI) algorithm for detecting cancer in digital breast tomosynthesis (DBT) could significantly improve detection accuracy and reduce health care costs worldwide.ObjectivesTo make training and ev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a8bb3df9af63065ca22b80acdc02e3c
https://doi.org/10.1001/jamanetworkopen.2023.0524
https://doi.org/10.1001/jamanetworkopen.2023.0524
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030872397
MICCAI (5)
MICCAI (5)
Detecting the specific locations of malignancy signs in a medical image is a non-trivial and time-consuming task for radiologists. A complex, 3D version of this task, was presented in the DBTex 2021 Grand Challenge on Digital Breast Tomosynthesis Les
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa6866820441369f3fe60ddf1a78f3ac
https://doi.org/10.1007/978-3-030-87240-3_74
https://doi.org/10.1007/978-3-030-87240-3_74
Autor:
Kristine Pysarenko, Pablo Gómez del Campo, Daniel Khapun, Alana A. Lewin, Linda Moy, Jungkyu Park, Yoel Shoshan, Sindhoora Murthy, Julia E. Goldberg, Robert Martí, Ella Barkan, Linda Du, Jakub Chłędowski, Ujas Parikh, Anastasia Plaunova, Krzysztof J. Geras, Sardius Chen, Alexandra Millet, Laura Heacock, Sushma Gaddam, Melanie Wegener, Eric H. Kim, Vadim Ratner, Beatriu Reig, Shalin Patel, Sana Hava, Jan Witowski, Stacey Wolfson, Michal Rosen-Zvi, Aviad Zlotnick, Jiyon Lee, Flora Gilboa-Solomon
Publikováno v:
Nature Machine Intelligence. 3:735-736
A new international competition aims to speed up the development of AI models that can assist radiologists in detecting suspicious lesions from hundreds of millions of pixels in 3D mammograms. The top three winning teams compare notes.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3db01a6dfb3f257c150bf6969fb0e791
https://doi.org/10.1038/s42256-021-00378-z
https://doi.org/10.1038/s42256-021-00378-z