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12 p, 4.0 MB |
Domain generalization in deep learning for contrast-enhanced imaging
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Sendra-Balcells, C. (Universitat de Barcelona) ;
Campello, Victor M (Universitat de Barcelona) ;
Martín-Isla, C. (Universitat de Barcelona) ;
Viladés Medel, David (Institut d'Investigació Biomèdica Sant Pau) ;
Descalzo, Martin (Institut d'Investigació Biomèdica Sant Pau) ;
Guala, Andrea (Hospital Universitari Vall d'Hebron) ;
Rodriguez-Palomares, Jose F (Hospital Universitari Vall d'Hebron) ;
Lekadir, K. (Universitat de Barcelona) ;
Universitat Autònoma de Barcelona
The domain generalization problem has been widely investigated in deep learning for non-contrast imaging over the last years, but it received limited attention for contrast-enhanced imaging. However, there are marked differences in contrast imaging protocols across clinical centers, in particular in the time between contrast injection and image acquisition, while access to multi-center contrast-enhanced image data is limited compared to available datasets for non-contrast imaging. [...]
2022 -  10.1016/j.compbiomed.2022.106052
Computers in Biology and Medicine, Vol. 149 (october 2022) , p. 106052
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12 p, 2.9 MB |
Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation : The MMs Challenge
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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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19 p, 1.3 MB |
Retinal Blood Vessels Segmentation using Fréchet PDF and MSMO Method
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Kumar Saroj, Sushil (MMMUT gorakhpur) ;
Kumar, Rakesh (Madan Mohan Malaviya University of Technology (Ïndia)) ;
Singh, Nagendra Pratap (NIT, Hamirpur)
Blood vessels of retina contain information about many severe diseases like glaucoma, hypertension, obesity, diabetes etc. Health professionals use this information to detect and diagnose these diseases. [...]
2022 - 10.5565/rev/elcvia.1453
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 21 Núm. 1 (2022) , p. 28-46 (Regular Issue)
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20 p, 756.0 KB |
Social Video Advertisement Replacement and its Evaluation in Convolutional Neural Networks
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Yang, Cheng (Auckland University of Technology (Nova Zelanda). Department of Electrical and Electronic Engineering) ;
Yu, Xiang (Auckland University of Technology (Nova Zelanda)) ;
Kumar, Arun (National Institute of Technology (Odisha, Índia). Department of Computer Science & Engineering) ;
Ali, G. G. Md. Nawaz (University of Charleston (Estats Units d'Amèrica). Department of Applied Computer Science) ;
Chong, Peter Han Joo (Auckland University of Technology (Nova Zelanda). Department of Electrical and Electronic Engineering) ;
Lam, Patrick (Auckland University of Technology (Nova Zelanda))
This paper introduces a method to use deep convolutional neural networks (CNNs) to automatically replace advertisement (AD) photo on social (or self-media) videos and provides the suitable evaluation method to compare different CNNs. [...]
2021 - 10.5565/rev/elcvia.1347
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 117-136 (Regular Issue)
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13 p, 6.4 MB |
Robust computer vision system for marbling meat segmentation
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Campos, Gabriel Fillipe Centini (Universidade Estadual de Londrina. Department of Computer Science) ;
Seixas Jr., José Luis (Eötvös Loránd University (Budapest, Hongria). Department of Data Science and Engineering) ;
Barbon, Ana Paula A. C. (Universidade Estadual de Londrina. Department of Zootechnology) ;
Felinto, Alan Salvany (Universidade Estadual de Londrina. Department of Computer Science) ;
Bridi, Ana Maria (Universidade Estadual de Londrina. Department of Zootechnology) ;
Barbon Jr., Sylvio (Universidade Estadual de Londrina. Department of Computer Science)
In this study, we developed a robust automatic computer vision system for marbling meat segmentation. Our approach can segment muscle fat in various marbled meat samples using images acquired with different quality devices in an uncontrolled environment, where there was external ambient light and artificial light; thus, professionals can apply this method without specialized knowledge in terms of sample treatments or equipment, as well as without disruption to normal procedures, thereby obtaining a robust solution. [...]
2020 - 10.5565/rev/elcvia.777
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 19 Núm. 1 (2020) , p. 15-27 (Regular Issue)
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