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ORCID9th Brainles/SWITCH@MICCAI 2023: Vancouver, BC, Canada
- Ujjwal Baid, Reuben Dorent, Sylwia Malec, Monika Pytlarz, Ruisheng Su
, Navodini Wijethilake, Spyridon Bakas, Alessandro Crimi:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 9th International Workshop, BrainLes 2023, and 3rd International Workshop, SWITCH 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8 and 12, 2023, Revised Selected Papers. Lecture Notes in Computer Science 14668, Springer 2024, ISBN 978-3-031-76159-1
BrainLes
- Bao Yang, Peng Yang, Zifeng Qiu, Yueyan Bian, Jiaqiang Li, Xiang Dong, Junlong Qu, Qi Yang, Baiying Lei:
Detection of Onset Time for Acute Ischemic Stroke Based on Multi-scale Features and Cross-Attention. 3-12 - Weijia Feng, Lingting Zhu, Lequan Yu:
Cheap Lunch for Medical Image Segmentation by Fine-Tuning SAM on Few Exemplars. 13-22 - Prantik Deb, Lalith Bharadwaj Baru, Kamalaker Dadi, Raju S. Bapi:
BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision. 23-35 - Yannick Suter, Flurina Schuhmacher, Ekin Ermis, Urspeter Knecht, Philippe Schucht, Roland Wiest, Mauricio Reyes:
Towards Radiomics-Based Automated Disease Progression Assessment for Glioblastoma Patients. 36-47 - Domen Preloznik, Ziga Spiclin:
Domain Unlearning Boosts Lesion Segmentation Performance on Seen and Unseen MR Scanner Data. 48-56 - Diana Waldmannstetter, Benedikt Wiestler, Julian Schwarting, Ivan Ezhov, Marie Metz, Spyridon Bakas, Bhakti Baheti, Satrajit Chakrabarty, Daniel Rueckert, Jan S. Kirschke, Rolf A. Heckemann, Marie Piraud, Bjoern H. Menze, Florian Kofler:
Primitive Simultaneous Optimization of Similarity Metrics for Image Registration. 57-68 - Aditya Kasliwal, Sankarshanaa Sagaram, Laven Srivastava, Pratinav Seth, Adil Khan:
ReFuSeg: Regularized Multi-modal Fusion for Precise Brain Tumour Segmentation. 69-80 - Hamza Daruger, David J. Brodsky, Baris Coskunuzer:
3D MRI Brain Tumor Diagnosis with Topological Descriptors. 81-94
SWITCH
- Weijin Xu, Zhuang Sha, Huihua Yang, Rongcai Jiang, Zhanying Li, Wentao Liu, Ruisheng Su:
An Automatic Cascaded Model for Hemorrhagic Stroke Segmentation and Hemorrhagic Volume Estimation. 97-105 - Theo Leuliet, Stefan Huwer, Bénédicte Maréchal, Veronica Ravano, Tobias Kober, Jonathan Rafael-Patino, Johannes Kaesmacher, Roland Wiest, Jonas Richiardi, Richard McKinley:
Deep Learning for Ischemic Penumbra Segmentation from MR Perfusion Maps: Robustness to the Deconvolution Algorithm. 106-114 - Marie Ulens, Jeroen Bertels, Ewout Heylen, Julie Lambert, Jelle Demeestere, Robin Lemmens, Dirk Vandermeulen, Frederik Maes:
From Brain Tissue Infarction at 24 Hours to Patient Functional Outcome at 90 Days Using Deep Learning. 115-123 - Ewout Heylen, Jeroen Bertels, Julie Lambert, Jelle Demeestere, Fredrik Ståhl, Åke Holmberg, Wim H. van Zwam, Charles B. L. M. Majoie, Aad van der Lugt, Robin Lemmens, Frederik Maes:
Functional Outcome Prediction in Acute Ischemic Stroke. 124-133 - Sjir J. C. Schielen, Danny H. Huynh, Bart A. J. M. Wagemans, Danny Ruijters, Wim H. van Zwam, Svitlana Zinger:
The Detection and Segmentation of Blush in the Lenticulostriate Territory. 134-143 - Frank te Nijenhuis, Ruisheng Su, Pieter Jan van Doormaal, Jeannette Hofmeijer, Jasper Martens, Wim H. van Zwam, Aad van der Lugt, Theo van Walsum:
Multimodal Deep Learning for Functional Outcome Prediction in Endovascular Therapy. 144-153 - Chayanin Tangwiriyasakul, Pedro Borges, Stefano Moriconi, Paul Wright, Yee-Haur Mah, James T. Teo, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Framework to Generate Perfusion Map from CT and CTA Images in Patients with Acute Ischemic Stroke: A Longitudinal and Cross-Sectional Study. 154-162
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