Michał Drożdżal
Michał Drożdżal
Fundamental AI Research at Meta
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Cited by
Cited by
The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation
S Jégou, M Drozdzal, D Vazquez, A Romero, Y Bengio
Proceedings of the IEEE conference on computer vision and pattern …, 2017
The importance of skip connections in biomedical image segmentation
M Drozdzal, E Vorontsov, G Chartrand, S Kadoury, C Pal
International workshop on deep learning in medical image analysis …, 2016
Deep learning: a primer for radiologists
G Chartrand, PM Cheng, E Vorontsov, M Drozdzal, S Turcotte, CJ Pal, ...
Radiographics 37 (7), 2113-2131, 2017
The liver tumor segmentation benchmark (lits)
P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ...
Medical Image Analysis 84, 102680, 2023
fastMRI: An open dataset and benchmarks for accelerated MRI
J Zbontar, F Knoll, A Sriram, T Murrell, Z Huang, MJ Muckley, A Defazio, ...
arXiv preprint arXiv:1811.08839, 2018
A benchmark for endoluminal scene segmentation of colonoscopy images
D Vázquez, J Bernal, FJ Sánchez, G Fernández-Esparrach, AM López, ...
Journal of healthcare engineering 2017 (1), 4037190, 2017
fastMRI: A publicly available raw k-space and DICOM dataset of knee images for accelerated MR image reconstruction using machine learning
F Knoll, J Zbontar, A Sriram, MJ Muckley, M Bruno, A Defazio, M Parente, ...
Radiology: Artificial Intelligence 2 (1), e190007, 2020
Learning normalized inputs for iterative estimation in medical image segmentation
M Drozdzal, G Chartrand, E Vorontsov, M Shakeri, L Di Jorio, A Tang, ...
Medical image analysis 44, 1-13, 2018
Inverse cooking: Recipe generation from food images
A Salvador, M Drozdzal, X Giró-i-Nieto, A Romero
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
Reducing uncertainty in undersampled MRI reconstruction with active acquisition
Z Zhang, A Romero, MJ Muckley, P Vincent, L Yang, M Drozdzal
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
Instance-conditioned gan
A Casanova, M Careil, J Verbeek, M Drozdzal, A Romero Soriano
Advances in Neural Information Processing Systems 34, 27517-27529, 2021
Generic feature learning for wireless capsule endoscopy analysis
S Seguí, M Drozdzal, G Pascual, P Radeva, C Malagelada, F Azpiroz, ...
Computers in biology and medicine 79, 163-172, 2016
Active MR k-space Sampling with Reinforcement Learning
L Pineda, S Basu, A Romero, R Calandra, M Drozdzal
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
Parameter prediction for unseen deep architectures
B Knyazev, M Drozdzal, GW Taylor, A Romero Soriano
Advances in Neural Information Processing Systems 34, 29433-29448, 2021
Categorization and segmentation of intestinal content frames for wireless capsule endoscopy
S Segui, M Drozdzal, F Vilarino, C Malagelada, F Azpiroz, P Radeva, ...
IEEE Transactions on Information Technology in Biomedicine 16 (6), 1341-1352, 2012
System and method for displaying motility events in an in vivo image stream
M Drozdzal, SS Mesquida, P Radeva, J Vitria, L Igual-Munoz, ...
US Patent 9,514,556, 2016
3d shape reconstruction from vision and touch
E Smith, R Calandra, A Romero, G Gkioxari, D Meger, J Malik, M Drozdzal
Advances in Neural Information Processing Systems 33, 14193-14206, 2020
Functional gut disorders or disordered gut function? Small bowel dysmotility evidenced by an original technique
C Malagelada, F De Lorio, S Segui, S Mendez, M Drozdzal, J Vitria, ...
Neurogastroenterology & Motility 24 (3), 223-e105, 2012
On the evaluation of conditional GANs
T DeVries, A Romero, L Pineda, GW Taylor, M Drozdzal
arXiv preprint arXiv:1907.08175, 2019
Classification of functional bowel disorders by objective physiological criteria based on endoluminal image analysis
C Malagelada, M Drozdzal, S Seguí, S Mendez, J Vitrià, P Radeva, ...
American Journal of Physiology-Gastrointestinal and Liver Physiology 309 (6 …, 2015
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