DeepISLES - Standalone software with GUI
Authors/Creators
- de la Rosa, Ezequiel1
- Reyes, Mauricio2
- Liew, Sook-Lei
- Hutton, Alexandre
- Wiest, Roland
- Kaesmacher, Johannes
- Hanning, Uta
- Hakim, Arsany
- Zubal, Richard
- Valenzuela, Waldo
- Robben, David
- Sima, Diana
- Anania, Vincenzo
- Brys, Arne
- Meakin, James
- Mickan, Anne
- Broocks, Gabriel
- Heitkamp, Christian
- Gao, Shengbo
- Liang, Kongming
- Zhang, Ziji
- Rahman Siddiquee, Md Mahfuzur
- Myronenko, Andriy
- Ashtari, Pooya
- Van Huffel, Sabine
- Jeong, Hyun-su
- Yoon, Chi-ho
- Kim, Chulhong
- Huo, Jiayu
- Ourselin, Sebastien
- Sparks, Rachel
- Clèrigues, Albert
- Oliver, Arnau
- Lladó, Xavier
- Chalcroft, Liam
- Pappas, Ioannis
- Bertels, Jeroen
- Heylen, Ewout
- Moreau, Juliette
- Hatami, Nima
- Frindel, Carole
- Qayyum, Abdul
- Mazher, Moona
- Puig, Domenec
- Lin, Shao-Chieh
- Juan, Chun-Jung Juan
- Hu, Tianxi
- Boone, Lyndon
- Goubran, Maged
- Liu, Yi-Jui
- Wegener, Susanne
- Kofler, Florian
- Ezhov, Ivan
- Shit,, Suprosanna
- Hernandez Petzsche, Moritz R.
- Müller, Michael
- Menze, Bjoern
- Kirschke, Jan
- Wiestler, Benedikt
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1.
University of Zurich
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2.
University of Bern
Description
Standalone version of DeepISLES including a graphical-user-interface. It allows single and batch mode MRI processing.
DeepISLES is a state-of-the art stroke lesion segmentation in MRI. Source git repository: https://github.com/ezequieldlrosa/DeepIsles
Linux-based. GPU required.
If you use this tool, please cite the following publications:
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de la Rosa, E., Reyes, M., Liew, S. L., Hutton, A., Wiest, R., Kaesmacher, J., ... & Wiestler, B. (2024).
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge.
arXiv:2403.19425 -
Hernandez Petzsche, M. R., de la Rosa, E., Hanning, U., Wiest, R., Valenzuela, W., Reyes, M., ... & Kirschke, J. S. (2022).
ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.
Scientific Data, 9(1), 762
Files
Files
(136.7 MB)
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