Dipòsit Digital de Documents de la UAB 3 registres trobats  La cerca s'ha fet en 0.02 segons. 
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12 p, 2.9 MB Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation : The MMs Challenge / Campello, Victor M. (Universitat de Barcelona. Departament de Matemàtiques i Informàtica) ; Gkontra, Polyxeni (Universitat de Barcelona. Departament de Matemàtiques i Informàtica) ; Izquierdo, Cristian (Universitat de Barcelona. Departament de Matemàtiques i Informàtica) ; Martin-Isla, Carlos (Universitat de Barcelona. Departament de Matemàtiques i Informàtica) ; Sojoudi, Alireza (Circle Cardiovascular Imaging Pvt. Ltd.) ; Full, Peter M. (German Cancer Research Center) ; Maier-Hein, Klaus (Division of Medical Image Computing. German Cancer Research Center) ; Zhang, Yao (Chinese Academy of Sciences. Institute of Computing Technology) ; He, Zhiqiang (Lenovo Ltd.) ; Ma, Jun (Nanjing University of Science and Technology) ; Parreno, Mario (Universitat Politècnica de València) ; Albiol, Alberto (Universitat Politècnica de València. iTeam Research Institute) ; Kong, Fanwei (University of California at Berkeley. Department of Mechanical Engineering) ; Shadden, Shawn C. (University of California at Berkeley. Department of Mechanical Engineeringy) ; Corral Acero, Jorge (Institute of Biomedical Engineering. Department of Engineering Science. University of Oxford) ; Sundaresan, Vaanathi (University of Oxford. Nuffield Department of Clinical Neurosciences) ; Saber, Mina (Research and Development Division. Intixel Company S.A.E.) ; Elattar, Mustafa (Research and Development Division. Intixel Company S.A.E.) ; Li, Hongwei (Department of Computer Science. Technische Universität München) ; Menze, Bjoern (Department of Computer Science. Technische Universität München) ; Khader, Firas (ARISTRA GmbH) ; Haarburger, Christoph (ARISTRA GmbH) ; Scannell, Cian M. (School of Biomedical Engineering and Imaging Sciences. King's College London) ; Veta, Mitko (Department of Biomedical Engineering. Eindhoven University of Technology) ; Carscadden, Adam (Department of Radiology and Diagnostic Imaging. University of Alberta) ; Punithakumar, Kumaradevan (Department of Radiology and Diagnostic Imaging. University of Alberta) ; Liu, Xiao (School of Engineering. The University of Edinburgh) ; Tsaftaris, Sotirios A. (School of Engineering. The University of Edinburgh) ; Huang, Xiaoqiong (School of Biomedical Engineering. Shenzhen University) ; Yang, Xin (School of Biomedical Engineering. Shenzhen University) ; Li, Lei (School of Biomedical Engineering. Shenzhen University) ; Zhuang, Xiahai (School of Data Science. Fudan University) ; Viladés Medel, David (Institut d'Investigació Biomèdica Sant Pau) ; Descalzo, Martin (Institut d'Investigació Biomèdica Sant Pau) ; Guala, Andrea (Hospital Universitari Vall d'Hebron. Institut de Recerca) ; Mura, Lucía La (Department of Advanced Biomedical Sciences. University of Naples Federico II) ; Friedrich, Matthias G. (Department of Medicine and Diagnostic Radiology. McGill University) ; Garg, Ria (Department of Medicine and Diagnostic Radiology. McGill University) ; Lebel, Julie (Department of Medicine and Diagnostic Radiology. McGill University) ; Henriques, Filipe. (Department of Cardiology. University Heart Vascular Center Hamburg) ; Karakas, Mahir (Department of Cardiology. University Heart Vascular Center Hamburg) ; Cavus, Ersin (Barts Heart Centre. Barts Health NHS Trust) ; Petersen, Steffen E. (Universitat de Barcelona. Departament de Matemàtiques i Informàtica) ; Escalera, Sergio (Hospital Universitari Vall d'Hebron. Institut de Recerca) ; Segui, Santi (Hospital Universitari Vall d'Hebron. Institut de Recerca) ; Rodriguez-Palomares, Jose F.. (Universitat de Barcelona. Departament de Matemàtiques i Informàtica) ; Lekadir, Karim (Universitat de Barcelona. Departament de Matemàtiques i Informàtica) ; Universitat Autònoma de Barcelona
The emergence of deep learning has considerably advanced the state-of-the-art in cardiac magnetic resonance (CMR) segmentation. Many techniques have been proposed over the last few years, bringing the accuracy of automated segmentation close to human performance. [...]
2021 - 10.1109/TMI.2021.3090082
IEEE Transactions on Medical Imaging, Vol. 40 Núm. 12 (january 2021) , p. 3543-3554  
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12 p, 7.7 MB Mosaic-Based Color-Transform Optimization for Lossy and Lossy-to-Lossless Compression of Pathology Whole-Slide Images / Hernández-Cabronero, Miguel (University of Warwick) ; Sánchez, Victor (University of Warwick) ; Marcellin, Michael W. (University of Arizona) ; Aulí Llinàs, Francesc (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions) ; Blanes Garcia, Ian (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions) ; Serra Sagristà, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
The use of whole-slide images (WSIs) in pathology entails stringent storage and transmission requirements because of their huge dimensions. Therefore, image compression is an essential tool to enable efficient access to these data. [...]
2019 - 10.1109/TMI.2018.2852685
IEEE Transactions on Medical Imaging, Vol. 38, Issue 1 (January 2019) , p. 21-32  
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11 p, 3.0 MB Analysis-driven lossy compression of DNA microarray images / Hernández Cabronero, Miguel (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions) ; Blanes Garcia, Ian (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions) ; Pinho, Armando J. (Universidade de Aveiro. DETI/IEETA) ; Marcellin, Michael W. (University of Arizona. Department of Electrical and Computer Engineering) ; Serra Sagristà, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
DNA microarrays are one of the fastest-growing new technologies in the field of genetic research, and DNA microarray images continue to grow in number and size. Since analysis techniques are under active and ongoing development, storage, transmission and sharing of DNA microarray images need be addressed, with compression playing a significant role. [...]
2016 - 10.1109/TMI.2015.2489262
Medical Imaging, IEEE Transactions, Vol. 35 Issue 2 (Feb. 2016) , p. 654-664  

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