Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Gur, Yaniv"'
Autor:
Kashyap, Satyananda, Karargyris, Alexandros, Wu, Joy, Gur, Yaniv, Sharma, Arjun, Wong, Ken C. L., Moradi, Mehdi, Syeda-Mahmood, Tanveer
Publikováno v:
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)
Deep learning has now become the de facto approach to the recognition of anomalies in medical imaging. Their 'black box' way of classifying medical images into anomaly labels poses problems for their acceptance, particularly with clinicians. Current
Externí odkaz:
http://arxiv.org/abs/2008.00363
Autor:
Syeda-Mahmood, Tanveer, Wong, Ken C. L., Gur, Yaniv, Wu, Joy T., Jadhav, Ashutosh, Kashyap, Satyananda, Karargyris, Alexandros, Pillai, Anup, Sharma, Arjun, Syed, Ali Bin, Boyko, Orest, Moradi, Mehdi
Obtaining automated preliminary read reports for common exams such as chest X-rays will expedite clinical workflows and improve operational efficiencies in hospitals. However, the quality of reports generated by current automated approaches is not ye
Externí odkaz:
http://arxiv.org/abs/2007.13831
Autor:
Wong, Ken C. L., Moradi, Mehdi, Wu, Joy, Pillai, Anup, Sharma, Arjun, Gur, Yaniv, Ahmad, Hassan, Chowdary, Minnekanti Sunil, J, Chiranjeevi, Polaka, Kiran Kumar Reddy, Wunnava, Venkateswar, Reddy, DC, Syeda-Mahmood, Tanveer
We propose a novel deep neural network architecture for normalcy detection in chest X-ray images. This architecture treats the problem as fine-grained binary classification in which the normal cases are well-defined as a class while leaving all other
Externí odkaz:
http://arxiv.org/abs/2004.06147
Autor:
Syeda-Mahmood, Tanveer, Ahmad, Hassan M., Ansari, Nadeem, Gur, Yaniv, Kashyap, Satyananda, Karargyris, Alexandros, Moradi, Mehdi, Pillai, Anup, Sheshadri, Karthik, Wang, Weiting, Wong, Ken C. L., Wu, Joy T.
Chest X-rays are the most common diagnostic exams in emergency rooms and hospitals. There has been a surge of work on automatic interpretation of chest X-rays using deep learning approaches after the availability of large open source chest X-ray data
Externí odkaz:
http://arxiv.org/abs/1906.09336
Publikováno v:
Lecture Notes in Computer Science (LNCS 11070), Proceedings of Medical Image Computing & Computer Assisted Intervention (MICCAI 2018)
Medical image analysis practitioners have embraced big data methodologies. This has created a need for large annotated datasets. The source of big data is typically large image collections and clinical reports recorded for these images. In many cases
Externí odkaz:
http://arxiv.org/abs/1809.01610
Autor:
Ning, Lipeng, Laun, Frederik, Gur, Yaniv, DiBella, Edward V.R., Deslauriers-Gauthier, Samuel, Megherbi, Thinhinane, Ghosh, Aurobrata, Zucchelli, Mauro, Menegaz, Gloria, Fick, Rutger, St-Jean, Samuel, Paquette, Michael, Aranda, Ramon, Descoteaux, Maxime, Deriche, Rachid, O’Donnell, Lauren, Rathi, Yogesh
Publikováno v:
In Medical Image Analysis December 2015 26(1):316-331
Akademický článek
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Akademický článek
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Autor:
Gur, Yaniv1 yanivg@post.tau.ac.il, Pasternak, Ofer2 oferpas@post.tau.ac.il, Sochen, Nir1 sochen@post.tau.ac.il
Publikováno v:
International Journal of Computer Vision. Dec2009, Vol. 85 Issue 3, p211-222. 12p. 6 Color Photographs, 1 Black and White Photograph, 1 Diagram, 1 Chart.