Zobrazeno 1 - 10
of 460
pro vyhledávání: '"Alan L. Yuille"'
Publikováno v:
Pattern Recognition Letters. 163:152-158
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fffd0837917dea26c650c8d79c4e9fb
https://doi.org/10.1016/j.patrec.2022.09.022
https://doi.org/10.1016/j.patrec.2022.09.022
Autor:
Jiefeng Gan, Hanchen Wang, Hui Yu, Zitong He, Wenjuan Zhang, Ke Ma, Lianghui Zhu, Yutong Bai, Zongwei Zhou, Alan L. Yuille, Xiang Bai, Mingwei Wang, Dehua Yang, Yanyan Chen, Guoan Chen, Joan Lasenby, Chao Cheng, Jia Wu, Jianjun Zhang, Xinggang Wang, Yaobing Chen, Guoping Wang, Tian Xia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ced9f9b26fb048b1260284099be4ae5c
https://doi.org/10.2139/ssrn.4361627
https://doi.org/10.2139/ssrn.4361627
Autor:
Yingda Xia, Qihang Yu, Linda Chu, Satomi Kawamoto, Seyoun Park, Fengze Liu, Jieneng Chen, Zhuotun Zhu, Bowen Li, Zongwei Zhou, Yongyi Lu, Yan Wang, Wei Shen, Lingxi Xie, Yuyin Zhou, Christopher Wolfgang, Ammar Javed, Daniel Fadaei Fouladi, Shahab Shayesteh, Jefferson Graves, Alejandra Blanco, Eva S. Zinreich, Miriam Klauss, Philipp Mayer, Benedict Kinny-Köster, Kenneth Kinzler, Ralph H. Hruban, Bert Vogelstein, Alan L. Yuille, Elliot K. Fishman
Tens of millions of abdominal images are obtained with computed tomography (CT) in the U.S. each year but pancreatic cancers are sometimes not initially detected in these images. We here describe a suite of algorithms (named FELIX) that can recognize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8064ed4a99dcb593ecdc14b8b085a411
https://doi.org/10.1101/2022.09.24.22280071
https://doi.org/10.1101/2022.09.24.22280071
Autor:
Satomi Kawamoto, Ralph H. Hruban, Alan L. Yuille, Seyoun Park, Linda C. Chu, Elliot K. Fishman
Publikováno v:
Current Problems in Diagnostic Radiology. 50:540-550
Computed tomography is the most commonly used imaging modality to detect and stage pancreatic cancer. Previous advances in pancreatic cancer imaging have focused on optimizing image acquisition parameters and reporting standards. However, current sta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57e356dc9c6fa1a42a4d113ac3869610
https://doi.org/10.1067/j.cpradiol.2020.08.002
https://doi.org/10.1067/j.cpradiol.2020.08.002
Publikováno v:
IEEE Trans Med Imaging
The spleen is one of the most commonly injured solid organs in blunt abdominal trauma. The development of automatic segmentation systems from multi-phase CT for splenic vascular injury can augment severity grading for improving clinical decision supp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d981eddfb6d294a62cfafa6090dd4fb
https://europepmc.org/articles/PMC9167782/
https://europepmc.org/articles/PMC9167782/
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 43:404-419
Age estimation from facial images is typically cast as a label distribution learning or regression problem, since aging is a gradual progress. Its main challenge is the facial feature space w.r.t. ages is inhomogeneous, due to the large variation in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d37959f90c4cdf3337c3b282278ab6ac
https://doi.org/10.1109/tpami.2019.2937294
https://doi.org/10.1109/tpami.2019.2937294
Autor:
Alan L. Yuille, Chenxi Liu
Publikováno v:
International Journal of Computer Vision. 129:781-802
This is an opinion paper about the strengths and weaknesses of Deep Nets for vision. They are at the heart of the enormous recent progress in artificial intelligence and are of growing importance in cognitive science and neuroscience. They have had m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90bf8d2a45fd0034bbaad9daa27ea9cf
https://doi.org/10.1007/s11263-020-01405-z
https://doi.org/10.1007/s11263-020-01405-z
Publikováno v:
International Journal of Computer Vision. 129:736-760
Computer vision systems in real-world applications need to be robust to partial occlusion while also being explainable. In this work, we show that black-box deep convolutional neural networks (DCNNs) have only limited robustness to partial occlusion.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e09b2a926270324fb0d932aae4f66f61
https://doi.org/10.1007/s11263-020-01401-3
https://doi.org/10.1007/s11263-020-01401-3
Autor:
Bert Vogelstein, Jin He, Seyoun Park, Christopher L. Wolfgang, Shahab Shayesteh, Kenneth W. Kinzler, E K Fishman, Saeed Ghandili, Linda C. Chu, Satomi Kawamoto, Alan L. Yuille, Daniel Fadaei Fouladi, Richard A. Burkhart, Ralph H. Hruban
Publikováno v:
Diagnostic and Interventional Imaging. 101:555-564
Purpose The purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC). Materials and Methods
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::669cd0aff212311eb74bdb49516ca2c9
https://doi.org/10.1016/j.diii.2020.03.002
https://doi.org/10.1016/j.diii.2020.03.002
Autor:
Satomi Kawamoto, Berkan Solmaz, Alan L. Yuille, Ralph H. Hruban, Linda C. Chu, Seyoun Park, Elliot K. Fishman
Publikováno v:
Abdominal Radiology. 45:2469-2475
The purpose of this study is to evaluate diagnostic performance of a commercially available radiomics research prototype vs. an in-house radiomics software in the binary classification of CT images from patients with pancreatic ductal adenocarcinoma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7255daa4d414e0851ebf196bf735915
https://doi.org/10.1007/s00261-020-02556-w
https://doi.org/10.1007/s00261-020-02556-w