Kaisar Kushibar
Cited by
Cited by
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review
J Bernal, K Kushibar, DS Asfaw, S Valverde, A Oliver, R Martí, X Lladó
Artificial intelligence in medicine 95, 64-81, 2019
Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features
K Kushibar, S Valverde, S González-Villà, J Bernal, M Cabezas, A Oliver, ...
Medical image analysis 48, 177-186, 2018
Quantitative analysis of patch-based fully convolutional neural networks for tissue segmentation on brain magnetic resonance imaging
J Bernal, K Kushibar, M Cabezas, S Valverde, A Oliver, X Lladó
IEEE Access 7, 89986-90002, 2019
Supervised domain adaptation for automatic sub-cortical brain structure segmentation with minimal user interaction
K Kushibar, S Valverde, S Gonzalez-Villa, J Bernal, M Cabezas, A Oliver, ...
Scientific reports 9 (1), 1-15, 2019
Improving the detection of autism spectrum disorder by combining structural and functional MRI information
M Rakić, M Cabezas, K Kushibar, A Oliver, X Lladó
NeuroImage: Clinical 25, 102181, 2020
Face recognition using artificial neural networks in parallel architecture
B Omarov, A Suliman, K Kushibar
Survival prediction using ensemble tumor segmentation and transfer learning
M Cabezas, S Valverde, S González-Villà, A Clérigues, M Salem, ...
arXiv preprint arXiv:1810.04274, 2018
A hybrid slam and object recognition system for pepper robot
P Ardón, K Kushibar, S Peng
arXiv preprint arXiv:1903.00675, 2019
Data preparation for artificial intelligence in medical imaging: a comprehensive guide to open-access platforms and tools
O Diaz, K Kushibar, R Osuala, A Linardos, L Garrucho, L Igual, P Radeva, ...
Physica Medica 83, 25-37, 2021
Generating Longitudinal Atrophy Evaluation Datasets on Brain Magnetic Resonance Images Using Convolutional Neural Networks and Segmentation Priors
J Bernal, S Valverde, K Kushibar, M Cabezas, A Oliver, X Llado
Neuroinformatics, 1-16, 2021
Ensemble of convolutional neural networks for acute stroke anatomy differentiation
A Clèrigues, S Valverde, J Bernal, K Kushibar, M Cabezas, A Oliver, ...
International MICCAI Brainlesion Workshop, 2018
A Review of Generative Adversarial Networks in Cancer Imaging: New Applications, New Solutions
R Osuala, K Kushibar, L Garrucho, A Linardos, Z Szafranowska, S Klein, ...
arXiv preprint arXiv:2107.09543, 2021
MR brain segmentation using an ensemble of multi-path u-shaped convolutional neural networks and tissue segmentation priors
J Bernal, M Salem, K Kushibar, A Clèrigues, S Valverde, M Cabezas, ...
Accessed: Feb 20, 2019, 2018
FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Future Medical Imaging
K Lekadira, R Osuala, C Gallin, N Lazrak, K Kushibar, G Tsakou, S Aussó, ...
arXiv preprint arXiv:2109.09658, 2021
Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular Disease
A Linardos, K Kushibar, S Walsh, P Gkontra, K Lekadir
arXiv preprint arXiv:2107.03901, 2021
Transductive Transfer Learning for Domain Adaptation in Brain Magnetic Resonance Image Segmentation
K Kushibar, M Salem, S Valverde, À Rovira, J Salvi, A Oliver, X Lladó
Frontiers in Neuroscience 15, 2021
Automatic segmentation of brain structures in magnetic resonance images using deep learning techniques
K Kushibar
Universitat de Girona, 2020
Automatic brain tissue segmentation in patients with Multiple Sclerosis using Convolutional Neural Networks
J Bernal, K Kushibar, S Valverde, X Lladó, A Oliver
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