Multi-task deep learning for glaucoma detection from color fundus images

Autor: Lucas Pascal, Oscar J. Perdomo, Xavier Bost, Benoit Huet, Sebastian Otálora, Maria A. Zuluaga

Publikováno v: Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)

Abstract Glaucoma is an eye condition that leads to loss of vision and blindness if not diagnosed in time. Diagnosis requires human experts to estimate in a limited time subtle changes in the shape of the optic disc from retinal fundus images. Deep l

Externí odkaz: https://doaj.org/article/9b07bc8175674173bcaef4bdf4346910

From Accuracy to Reliability and Robustness in Cardiac Magnetic Resonance Image Segmentation: A Review

Autor: Francesco Galati, Sébastien Ourselin, Maria A. Zuluaga

Publikováno v: Applied Sciences, Vol 12, Iss 8, p 3936 (2022)

Since the rise of deep learning (DL) in the mid-2010s, cardiac magnetic resonance (CMR) image segmentation has achieved state-of-the-art performance. Despite achieving inter-observer variability in terms of different accuracy performance measures, vi

Externí odkaz: https://doaj.org/article/2a2279df490e4247bdd64c4554a62796

DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams

Autor: Yue Lu, Renjie Wu, Abdullah Mueen, Maria A. Zuluaga, Eamonn Keogh

Publikováno v: Data Mining and Knowledge Discovery. 37:627-669

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6d855161e9e3aa8af8181414b9a27345
https://doi.org/10.1007/s10618-022-00911-7

Deep Learning Segmentation of the Right Ventricle in Cardiac MRI:The M&Ms challenge

Autor: Carlos Martín-Isla, Víctor M. Campello, Cristian Izquierdo, Kaisar Kushibar, Carla Sendra-Balcells, Polyxeni Gkontra, Alireza Sojoudi, Mitchell J Fulton, Tewodros Weldebirhan Arega, Kumaradevan Punithakumar, Lei Li, Xiaowu Sun, Yasmina Al Khalil, Di Liu, Sana Jabbar, Sandro Queirós, Francesco Galati, Moona Mazher, Zheyao Gao, Marcel Beetz, Lennart Tautz, Christoforos Galazis, Marta Varela, Markus Hullebrand, Vicente Grau, Xiahai Zhuang, Domenec Puig, Maria A. Zuluaga, Hassan Mohy-ud-Din, Dimitris Metaxas, Marcel Breeuwer, Rob J. van der Geest, Michelle Noga, Stephanie Bricq, Mark E. Rentschler, Andrea Guala, Steffen E. Petersen, Sergio Escalera, José F. Rodríguez Palomares, Karim Lekadir

Publikováno v: Martin-Isla, C, Campello, V M, Izquierdo, C, Kushibar, K, Sendra-Balcells, C, Gkontra, P, Sojoudi, A, Fulton, M J, Arega, T W, Punithakumar, K, Li, L, Sun, X, Khalil, Y A, Liu, D, Jabbar, S, Queiros, S, Galati, F, Mazher, M, Gao, Z, Beetz, M, Tautz, L, Galazis, C, Varela, M, Hullebrand, M, Grau, V, Zhuang, X, Puig, D, Zuluaga, M A, Mohy-ud-Din, H, Metaxas, D, Breeuwer, M, Geest, R J V D, Noga, M, Bricq, S, Rentschler, M E, Guala, A, Petersen, S E, Escalera, S, Palomares, J F R & Lekadir, K 2023, ' Deep Learning Segmentation of the Right Ventricle in Cardiac MRI : The M &Ms challenge ', IEEE Journal of Biomedical and Health Informatics, pp. 1-14 . https://doi.org/10.1109/JBHI.2023.3267857

In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32a6c9c7985326e535eda2261dc13b51
https://vbn.aau.dk/da/publications/12cc1dcd-8442-48eb-99a4-807c7dd00d98

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.