Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Srijay Deshpande"'
Autor:
Johnathan Pocock, Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Srijay Deshpande, Giorgos Hadjigeorghiou, Adam Shephard, Raja Muhammad Saad Bashir, Mohsin Bilal, Wenqi Lu, David Epstein, Fayyaz Minhas, Nasir M. Rajpoot, Shan E Ahmed Raza
Publikováno v:
Communications Medicine, Vol 2, Iss 1, Pp 1-14 (2022)
Pocock, Graham et al. present TIAToolbox, a Python toolbox for computational pathology. The extendable library can be used for data loading, pre-processing, model inference, post-processing, and visualization.
Externí odkaz:
https://doaj.org/article/75c369f7e3674cc192d52f44add4ced6
Autor:
Oscar Acosta, Simon Arridge, Anais Barateau, Riccardo Barbano, Julien Bert, Ninon Burgos, Hu Chen, Kevin T. Chen, Xiaoran Chen, Li Cheng, Jae Hyuk Choi, Hilda Chourak, Walter J. Curran, Renaud de Crevoisier, Srijay Deshpande, Blake E. Dewey, Jason Dowling, Ivana Drobnjak, Jan Ehrhardt, Dennis Eschweiler, Alejandro F. Frangi, Mark Graham, Peter Greer, Shuo Han, Yufan He, Juan Eugenio Iglesias, Mark Jenkinson, Bangti Jin, Wenchi Ke, Charles Kervrann, Ender Konukoglu, Violeta Kovacheva, Claes N. Ladefoged, Ina Laube, Yang Lei, Andrea Leo, Bowen Li, Huiqi Li, Tian Liu, Yihao Liu, Matteo Mancini, Fayyaz Minhas, Tereza Nečasová, Dong Nie, Jean-Claude Nunes, Laura O'Connor, Ilkay Oksuz, Anders B. Olin, Jerry L. Prince, Richard L.J. Qiu, Nasir Rajpoot, Parnesh Raniga, Nishant Ravikumar, Samuel W. Remedios, Pekka Ruusuvuori, David Sarrut, Johannes Stegmaier, David Svoboda, Ryutaro Tanno, Sotirios A. Tsaftaris, Vladimír Ulman, Gabriele Valvano, Tonghe Wang, Xuyun Wen, David Wiesner, Matthias Wilms, Yan Xia, Xiaofeng Yang, Greg Zaharchuk, Hui Zhang, Yi Zhang, Can Zhao, He Zhao, Lianrui Zuo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b44b27cc340c3c75307c529f2c431a63
https://doi.org/10.1016/b978-0-12-824349-7.00006-2
https://doi.org/10.1016/b978-0-12-824349-7.00006-2
Autor:
Johnathan Pocock, Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Srijay Deshpande, Giorgos Hadjigeorghiou, Adam Shephard, Raja Muhammad Saad Bashir, Mohsin Bilal, Wenqi Lu, David Epstein, Fayyaz Minhas, Nasir M. Rajpoot, Shan E Ahmed Raza
Computational Pathology (CPath) has seen rapid growth in recent years, driven by advanced deep learning (DL) algorithms. These algorithms typically share the same sequence of steps. However, due to the sheer size and complexity of handling large mult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db028862c4c7cb9e9b9d7059a69ee1ee
https://doi.org/10.1101/2021.12.23.474029
https://doi.org/10.1101/2021.12.23.474029
Publikováno v:
Computing and Informatics. 38:473-496
Materialized views are important for optimizing Business Intelligence (BI) systems when they are designed without data cubes. Selecting candidate queries from large number of queries for materialized views is a challenging task. Most of the work done
Publikováno v:
Medical image analysis. 77
Automated synthesis of histology images has several potential applications including the development of data-efficient deep learning algorithms. In the field of computational pathology, where histology images are large in size and visual context is c
Publikováno v:
Simulation and Synthesis in Medical Imaging ISBN: 9783030595197
SASHIMI@MICCAI
SASHIMI@MICCAI
The construction of large tissue images is a challenging task in the field of generative modeling of histopathology images. Such synthetic images can be used for development and evaluation of various types of deep learning methods. However, memory an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f08360cf69ee53fd8ce6ed664fb99a92
https://doi.org/10.1007/978-3-030-59520-3_17
https://doi.org/10.1007/978-3-030-59520-3_17
Publikováno v:
SIGSPATIAL/GIS
Several emerging applications such as traffic management and urban emergency response systems often need to identify groups from recent window of the moving object data. These requirements mandate algorithmic solutions that are time and memory effici