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07/31/2023
Framing image registration as a landmark detection problem for better representation of clinical relevance
Nowadays, registration methods are typically evaluated based on sub-reso...
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05/30/2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)
Gliomas are the most common type of primary brain tumors. Although gliom...
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05/26/2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)
Pediatric tumors of the central nervous system are the most common cause...
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05/15/2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)
Automated brain tumor segmentation methods are well established, reachin...
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05/15/2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting
A myriad of algorithms for the automatic analysis of brain MR images is ...
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05/12/2023
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma
Meningiomas are the most common primary intracranial tumor in adults and...
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04/04/2023
Primitive Simultaneous Optimization of Similarity Metrics for Image Registration
Even though simultaneous optimization of similarity metrics represents a...
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12/31/2022
Approaching Peak Ground Truth
Machine learning models are typically evaluated by computing similarity ...
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06/14/2022
ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset
Magnetic resonance imaging (MRI) is a central modality for stroke imagin...
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05/17/2022
blob loss: instance imbalance aware loss functions for semantic segmentation
Deep convolutional neural networks have proven to be remarkably effectiv...
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05/09/2022
A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling
Solving the inverse problem is the key step in evaluating the capacity o...
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04/05/2022
A Dempster-Shafer approach to trustworthy AI with application to fetal brain MRI segmentation
Deep learning models for medical image segmentation can fail unexpectedl...
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11/16/2021
FedCostWAvg: A new averaging for better Federated Learning
We propose a simple new aggregation strategy for federated learning that...
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11/07/2021
Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling
Current treatment planning of patients diagnosed with brain tumor could ...
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09/03/2021
Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations
Fast and accurate solutions of time-dependent partial differential equat...
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03/10/2021
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient
In this study, we explore quantitative correlates of qualitative human e...
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09/09/2020
Real-time Bayesian personalization via a learnable brain tumor growth model
Modeling of brain tumor dynamics has the potential to advance therapeuti...
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04/22/2020
Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective
Exploiting learning algorithms under scarce data regimes is a limitation...
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07/01/2019
Neural parameters estimation for brain tumor growth modeling
Understanding the dynamics of brain tumor progression is essential for o...
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04/29/2019