Kaisar Kushibar

According to our database, Kaisar Kushibar authored at least 22 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MAMA-MIA: A Large-Scale Multi-Center Breast Cancer DCE-MRI Benchmark Dataset with Expert Segmentations.

Lidia Garrucho, Claire-Anne Reidel, Kaisar Kushibar, Smriti Joshi, Richard Osuala, Apostolia Tsirikoglou, Maciej Bobowicz, Javier del Riego, Alessandro Catanese, Katarzyna Gwozdziewicz, Maria-Laura Cosaka, Pasant M. Abo-Elhoda, Sara W. Tantawy, Shorouq S. Sakrana, Norhan O. Shawky-Abdelfatah, Amr Muhammad Abdo-Salem, Androniki Kozana, Eugen Divjak, Gordana Ivanac, Katerina Nikiforaki, Michail E. Klontzas, Rosa García-Dosdá, Meltem Gulsun-Akpinar, Oguz Lafci, Ritse Mann, Carlos Martín-Isla, Fred W. Prior, Kostas Marias, Martijn P. A. Starmans, Fredrik Strand, Oliver Díaz, Laura Igual, Karim Lekadir

CoRR, 2024

Debiasing Cardiac Imaging with Controlled Latent Diffusion Models.

Grzegorz Skorupko, Richard Osuala, Zuzanna Szafranowska, Kaisar Kushibar, Nay Aung, Steffen E. Petersen, Karim Lekadir, Polyxeni Gkontra

CoRR, 2024

Towards Learning Contrast Kinetics with Multi-condition Latent Diffusion Models.

Richard Osuala, Daniel M. Lang, Preeti Verma, Smriti Joshi, Apostolia Tsirikoglou, Grzegorz Skorupko, Kaisar Kushibar, Lidia Garrucho, Walter H. L. Pinaya, Oliver Díaz, Julia A. Schnabel, Karim Lekadir

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

2023

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

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 F. Queiros, Francesco Galati, Moona Mazher, Zheyao Gao, Marcel Beetz, Lennart Tautz, Christoforos Galazis, Marta Varela, Markus Hüllebrand, Vicente Grau, Xiahai Zhuang, Domenec Puig, Maria A. Zuluaga, Hassan Mohy-ud-Din, Dimitris N. Metaxas, Marcel Breeuwer, Rob J. van der Geest, Michelle Noga, Stéphanie Bricq, Mark E. Rentschler, Andrea Guala, Steffen E. Petersen, Sergio Escalera, José F. Rodríguez Palomares, Karim Lekadir

IEEE J. Biomed. Health Informatics, July, 2023

Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging.

Richard Osuala, Kaisar Kushibar, Lidia Garrucho, Akis Linardos, Zuzanna Szafranowska, Stefan Klein, Ben Glocker, Oliver Díaz, Karim Lekadir

Medical Image Anal., 2023

Revisiting Skin Tone Fairness in Dermatological Lesion Classification.

Thorsten Kalb, Kaisar Kushibar, Celia Cintas, Karim Lekadir, Oliver Díaz, Richard Osuala

Proceedings of the Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, 2023

2022

medigan: A Python Library of Pretrained Generative Models for Enriched Data Access in Medical Imaging.

Richard Osuala, Grzegorz Skorupko, Noussair Lazrak, Lidia Garrucho, Eloy García, Smriti Joshi, Socayna Jouide, Michael W. Rutherford, Fred W. Prior, Kaisar Kushibar, Oliver Díaz, Karim Lekadir

CoRR, 2022

High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection.

Lidia Garrucho, Kaisar Kushibar, Richard Osuala, Oliver Díaz, Alessandro Catanese, Javier del Riego, Maciej Bobowicz, Fredrik Strand, Laura Igual, Karim Lekadir

CoRR, 2022

Sharing Generative Models Instead of Private Data: A Simulation Study on Mammography Patch Classification.

Zuzanna Szafranowska, Richard Osuala, Bennet Breier, Kaisar Kushibar, Karim Lekadir, Oliver Díaz

CoRR, 2022

Domain generalization in deep learning based mass detection in mammography: A large-scale multi-center study.

Lidia Garrucho, Kaisar Kushibar, Socayna Jouide, Oliver Díaz, Laura Igual, Karim Lekadir

Artif. Intell. Medicine, 2022

Layer Ensembles: A Single-Pass Uncertainty Estimation in Deep Learning for Segmentation.

Kaisar Kushibar, Víctor M. Campello, Lidia Garrucho, Akis Linardos, Petia Radeva, Karim Lekadir

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Generating Longitudinal Atrophy Evaluation Datasets on Brain Magnetic Resonance Images Using Convolutional Neural Networks and Segmentation Priors.

José Bernal, Sergi Valverde, Kaisar Kushibar, Mariano Cabezas, Arnau Oliver, Xavier Lladó

Neuroinformatics, 2021

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging.

Karim Lekadir, Richard Osuala, Catherine Gallin, Noussair Lazrak, Kaisar Kushibar, Gianna Tsakou, Susanna Aussó, Leonor Cerdá Alberich, Konstantinos Marias, Manolis Tsiknakis, Sara Colantonio, Nickolas Papanikolaou, Zohaib Salahuddin, Henry C. Woodruff, Philippe Lambin, Luis Martí-Bonmatí

CoRR, 2021

A Review of Generative Adversarial Networks in Cancer Imaging: New Applications, New Solutions.

Richard Osuala, Kaisar Kushibar, Lidia Garrucho, Akis Linardos, Zuzanna Szafranowska, Stefan Klein, Ben Glocker, Oliver Díaz, Karim Lekadir

CoRR, 2021

Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular Disease.

Akis Linardos, Kaisar Kushibar, Sean Walsh, Polyxeni Gkontra, Karim Lekadir

CoRR, 2021

Center Dropout: A Simple Method for Speed and Fairness in Federated Learning.

Akis Linardos, Kaisar Kushibar, Karim Lekadir

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

2020

Automatic segmentation of brain structures in magnetic resonance images using deep learning techniques.

Kaisar Kushibar

PhD thesis, 2020

2019

A Hybrid SLAM and Object Recognition System for Pepper Robot.

Paola Ardón, Kaisar Kushibar, Songyou Peng

CoRR, 2019

Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review.

José Bernal, Kaisar Kushibar, Daniel S. Asfaw, Sergi Valverde, Arnau Oliver, Robert Martí, Xavier Lladó

Artif. Intell. Medicine, 2019

Quantitative Analysis of Patch-Based Fully Convolutional Neural Networks for Tissue Segmentation on Brain Magnetic Resonance Imaging.

José Bernal, Kaisar Kushibar, Mariano Cabezas, Sergi Valverde, Arnau Oliver, Xavier Lladó

IEEE Access, 2019

2018

Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features.

Kaisar Kushibar, Sergi Valverde, Sandra González-Villà, José Bernal, Mariano Cabezas, Arnau Oliver, Xavier Lladó

Medical Image Anal., 2018

Survival prediction using ensemble tumor segmentation and transfer learning.

Mariano Cabezas, Sergi Valverde, Sandra González-Villà, Albert Clérigues, Mostafa Salem, Kaisar Kushibar, José Bernal, Arnau Oliver, Xavier Lladó

CoRR, 2018