Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Humayun Irshad"'
Autor:
Katherine Tian, Christopher A Rubadue, Douglas I Lin, Mitko Veta, Michael E Pyle, Humayun Irshad, Yujing J Heng
Publikováno v:
PLoS ONE, Vol 14, Iss 10, p e0222641 (2019)
We developed an automated 2-tiered Fuhrman's grading system for clear cell renal cell carcinoma (ccRCC). Whole slide images (WSI) and clinical data were retrieved for 395 The Cancer Genome Atlas (TCGA) ccRCC cases. Pathologist 1 reviewed and selected
Externí odkaz:
https://doaj.org/article/de403329d548411181fbb3158d08342b
Autor:
Fei Dong, Humayun Irshad, Eun-Yeong Oh, Melinda F Lerwill, Elena F Brachtel, Nicholas C Jones, Nicholas W Knoblauch, Laleh Montaser-Kouhsari, Nicole B Johnson, Luigi K F Rao, Beverly Faulkner-Jones, David C Wilbur, Stuart J Schnitt, Andrew H Beck
Publikováno v:
PLoS ONE, Vol 9, Iss 12, p e114885 (2014)
The categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced pathologists. The development of computational tools t
Externí odkaz:
https://doaj.org/article/844119d98e8d4658b32246632a97cbb3
Autor:
Ludovic Roux, Daniel Racoceanu, Nicolas Loménie, Maria Kulikova, Humayun Irshad, Jacques Klossa, Frédérique Capron, Catherine Genestie, Gilles Le Naour, Metin N Gurcan
Publikováno v:
Journal of Pathology Informatics, Vol 4, Iss 1, Pp 8-8 (2013)
Introduction: In the framework of the Cognitive Microscope (MICO) project, we have set up a contest about mitosis detection in images of H and E stained slides of breast cancer for the conference ICPR 2012. Mitotic count is an important parameter for
Externí odkaz:
https://doaj.org/article/0f2c071cee424368ac410d7f82695588
Autor:
Humayun Irshad
Publikováno v:
Journal of Pathology Informatics, Vol 4, Iss 1, Pp 10-10 (2013)
Context: According to Nottingham grading system, mitosis count plays a critical role in cancer diagnosis and grading. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Aims: The aim is to improve th
Externí odkaz:
https://doaj.org/article/6c92ea3a40034f87a6c9e26ccda8cb68
Autor:
Humayun Irshad, Sepehr Jalali, Ludovic Roux, Daniel Racoceanu, Lim Joo Hwee, Gilles Le Naour, Frédérique Capron
Publikováno v:
Journal of Pathology Informatics, Vol 4, Iss 2, Pp 12-12 (2013)
Context: According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-re
Externí odkaz:
https://doaj.org/article/5fade186a20d465bafde3f2836de915a
Autor:
Humayun Irshad, Thomas Boot
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 ISBN: 9783030597184
MICCAI (4)
MICCAI (4)
Computer-aided detection or diagnosing support methods aims to improve breast cancer screening programs by helping radiologists to evaluate digital mammography (DM) exams. This system relates to the use of deep learning for automated detection and se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a730ea7fbd097e40a802bbb3779cfd0
https://doi.org/10.1007/978-3-030-59719-1_6
https://doi.org/10.1007/978-3-030-59719-1_6
Autor:
Andrew H. Beck, Astrid Weins, Stuart J. Schnitt, Benjamin Glass, Isaac E. Stillman, Eun-Young Oh, Fei Chen, Andreea Lucia Stancu, Vanda F. Torous, Humayun Irshad, Yongxin Zhao, Edward S. Boyden, Octavian Bucur, Marcello DiStasio
Publikováno v:
PMC
Nature biotechnology
Nature biotechnology
Expansion microscopy (ExM), a method for improving the resolution of light microscopy by physically expanding a specimen, has not been applied to clinical tissue samples. Here we report a clinically optimized form of ExM that supports nanoscale imagi
Autor:
Yujing J. Heng, Katherine Tian, Humayun Irshad, Michael E. Pyle, Douglas I. Lin, Christopher A. Rubadue, Mitko Veta
Publikováno v:
PLoS ONE, Vol 14, Iss 10, p e0222641 (2019)
PLoS ONE, 14(10):e0222641. Public Library of Science
PLoS ONE
PLoS ONE, 14(10):e0222641. Public Library of Science
PLoS ONE
We developed an automated 2-tiered Fuhrman’s grading system for clear cell renal cell carcinoma (ccRCC). Whole slide images (WSI) and clinical data were retrieved for 395 The Cancer Genome Atlas (TCGA) ccRCC cases. Pathologist 1 reviewed and select
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54cf318f4d94c47e2af7b86626bd0dc4
Autor:
Ugur Halici, Rishab Gargeya, Quincy Wong, Hady Ahmady Phoulady, David Tellez, Bram van Ginneken, Andrew H. Beck, Nico Karssemeijer, Jeroen van der Laak, Nassir Navab, Jonas Annuscheit, Leena Latonen, Kaisa Liimatainen, Talha Qaiser, Dayong Wang, Quirine F. Manson, Aoxiao Zhong, Shigeto Seno, Yee-Wah Tsang, Rui Venâncio, Ismael Serrano, Daniel Racoceanu, N. Stathonikos, Muhammad Shaban, Stefanie Demirci, M. Milagro Fernández-Carrobles, Babak Ehteshami Bejnordi, Matt Berseth, Mustafa Umit Oner, Geert Litjens, Kimmo Kartasalo, Hideo Matsuda, Maschenka Balkenhol, Huangjing Lin, Elia Bruni, Hao Chen, Seiryo Watanabe, A. Kalinovsky, Marcory C. R. F. van Dijk, Ami George, Nasir M. Rajpoot, Francisco Beca, Quanzheng Li, Meyke Hermsen, Mira Valkonen, Oscar Deniz, Alexei Vylegzhanin, Vitali Liauchuk, Ruqayya Awan, Mitko Veta, Korsuk Sirinukunwattana, Gloria Bueno, Peter Hufnagl, Christian Haß, Vassili Kovalev, Vitali Khvatkov, Rengul Cetin-Atalay, Humayun Irshad, Oren Kraus, Qi Dou, Pekka Ruusuvuori, Aditya Khosla, Bharti Mungal, Pheng-Ann Heng, Oscar Geessink, Paul J. van Diest, Shadi Albarqouni, Peter Bult, Yoichi Takenaka
Publikováno v:
JAMA Cardiology
JAMA Cardiology, American Medical Association 2017, 318, ⟨10.1001/jama.2017.14585⟩
Jama : Journal of the American Medical Association, 318, 2199-2210
JAMA Neurology, 318(22), 2199-2210. American Medical Association (AMA)
Jama : Journal of the American Medical Association, 318, 22, pp. 2199-2210
JAMA-The Journal of The American Medical Association, 318(22), 2199. American Medical Association
JAMA Cardiology, American Medical Association 2017, 318, ⟨10.1001/jama.2017.14585⟩
Jama : Journal of the American Medical Association, 318, 2199-2210
JAMA Neurology, 318(22), 2199-2210. American Medical Association (AMA)
Jama : Journal of the American Medical Association, 318, 22, pp. 2199-2210
JAMA-The Journal of The American Medical Association, 318(22), 2199. American Medical Association
IMPORTANCE: Application of deep learning algorithms to whole-slide pathology imagescan potentially improve diagnostic accuracy and efficiency. OBJECTIVE: Assess the performance of automated deep learning algorithms at detecting metastases in hematoxy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c5e2e1ebc60e746d57a0deffa5ee651b
https://hal.archives-ouvertes.fr/hal-03140979/document
https://hal.archives-ouvertes.fr/hal-03140979/document
Publikováno v:
2017 International Conference on Innovations in Electrical Engineering and Computational Technologies (ICIEECT).
Wireless sensors network is a network consists of sensors node, creating cluster and selection of cluster head is an issue for an efficient WSN. A new technique is proposed in this research which is termed as Wireless Active Sensors Network (WASN). W