default search action
8th Brainles@MICCAI 2022: Singapore
- Spyridon Bakas
, Alessandro Crimi
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13769, Springer 2023, ISBN 978-3-031-33841-0
BrainLes
- Florian Kofler, Ivan Ezhov, Lucas Fidon, Izabela Horvath, Ezequiel de la Rosa, John LaMaster, Hongwei Li, Tom Finck, Suprosanna Shit
Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings. 3-13 - Felix Meissen, Johannes C. Paetzold, Georgios Kaissis, Daniel Rueckert:
Unsupervised Anomaly Localization with Structural Feature-Autoencoders. 14-24 - Ahmed Ghorbel
Transformer Based Models for Unsupervised Anomaly Segmentation in Brain MR Images. 25-44 - Sebastian Otálora, Jonathan Rafael-Patino, Antoine Madrona, Elda Fischi Gomez
Weighting Schemes for Federated Learning in Heterogeneous and Imbalanced Segmentation Datasets. 45-56 - Jueqi Wang, Derek Berger, Erin L. Mazerolle, Othman Soufan, Jacob Levman:
Temporally Adjustable Longitudinal Fluid-Attenuated Inversion Recovery MRI Estimation / Synthesis for Multiple Sclerosis. 57-67 - Bhakti Baheti
Leveraging 2D Deep Learning ImageNet-trained Models for Native 3D Medical Image Analysis. 68-79 - Selene De Sutter
Probabilistic Tissue Mapping for Tumor Segmentation and Infiltration Detection of Glioma. 80-89 - Krzysztof Kotowski
Robustifying Automatic Assessment of Brain Tumor Progression from MRI. 90-101 - Wenting Duan, Lei Zhang, Jordan Colman, Giosue Gulli, Xujiong Ye:
MidFusNet: Mid-dense Fusion Network for Multi-modal Brain MRI Segmentation. 102-114 - Shiyu Lu
Semi-supervised Intracranial Aneurysm Segmentation with Selected Unlabeled Data. 115-123
BraTS
- Ramy A. Zeineldin
Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution. 127-137 - Jihoon Cho
Multi-modal Transformer for Brain Tumor Segmentation. 138-148 - Philippe Bouchet
An Efficient Cascade of U-Net-Like Convolutional Neural Networks Devoted to Brain Tumor Segmentation. 149-161 - Michal Futrega, Michal Marcinkiewicz, Pablo Ribalta:
Tuning U-Net for Brain Tumor Segmentation. 162-173 - Qingfan Hou, Zhuofei Wang, Jiao Wang, Jian Jiang, Yanjun Peng:
Diffraction Block in Extended nn-UNet for Brain Tumor Segmentation. 174-185 - Krzysztof Kotowski, Szymon Adamski, Bartosz Machura, Lukasz Zarudzki, Jakub Nalepa:
Infusing Domain Knowledge into nnU-Nets for Segmenting Brain Tumors in MRI. 186-194 - Ramtin Mojtahedi
Multi-modal Brain Tumour Segmentation Using Transformer with Optimal Patch Size. 195-204 - Md. Shibly Sadique
Brain Tumor Segmentation Using Neural Ordinary Differential Equations with UNet-Context Encoding Network. 205-215 - Jia-Wei Liao, Tsung-Ming Huang
An UNet-Based Brain Tumor Segmentation Framework via Optimal Mass Transportation Pre-processing. 216-228
BraTS-Reg
- Tony C. W. Mok, Albert C. S. Chung:
Robust Image Registration with Absent Correspondences in Pre-operative and Follow-Up Brain MRI Scans of Diffuse Glioma Patients. 231-240 - Marek Wodzinski
Unsupervised Method for Intra-patient Registration of Brain Magnetic Resonance Images Based on Objective Function Weighting by Inverse Consistency: Contribution to the BraTS-Reg Challenge. 241-251 - Christoph Großbröhmer
Employing ConvexAdam for BraTS-Reg. 252-261 - Luca Canalini, Jan Klein, Annika Gerken, Stefan Heldmann, Alessa Hering, Horst K. Hahn:
Iterative Method to Register Longitudinal MRI Acquisitions in Neurosurgical Context. 262-272 - Mingyuan Meng
Brain Tumor Sequence Registration with Non-iterative Coarse-To-Fine Networks and Dual Deep Supervision. 273-282
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-12-19 22:02 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: