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09/05/2023
A skeletonization algorithm for gradient-based optimization
The skeleton of a digital image is a compact representation of its topol...
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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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05/26/2023
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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04/24/2023
FedPIDAvg: A PID controller inspired aggregation method for Federated Learning
This paper presents FedPIDAvg, the winning submission to the Federated T...
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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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10/28/2022
Automated analysis of diabetic retinopathy using vessel segmentation maps as inductive bias
Recent studies suggest that early stages of diabetic retinopathy (DR) ca...
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09/14/2022
Landmark-free Statistical Shape Modeling via Neural Flow Deformations
Statistical shape modeling aims at capturing shape variations of an anat...
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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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03/19/2022
Relationformer: A Unified Framework for Image-to-Graph Generation
A comprehensive representation of an image requires understanding object...
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03/01/2022
A unified 3D framework for Organs at Risk Localization and Segmentation for Radiation Therapy Planning
Automatic localization and segmentation of organs-at-risk (OAR) in CT ar...
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12/24/2021
Generalized Wasserstein Dice Loss, Test-time Augmentation, and Transformers for the BraTS 2021 challenge
Brain tumor segmentation from multiple Magnetic Resonance Imaging (MRI) ...
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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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08/30/2021
Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience (VesselGraph)
Biological neural networks define the brain function and intelligence of...
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04/22/2021
METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Microscopy
Novel multimodal imaging methods are capable of generating extensive, su...
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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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03/06/2021
Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations
Radiomic representations can quantify properties of regions of interest ...
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03/04/2021
The MICCAI Hackathon on reproducibility, diversity, and selection of papers at the MICCAI conference
The MICCAI conference has encountered tremendous growth over the last ye...
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10/29/2020
A comparison of automatic multi-tissue segmentation methods of the human fetal brain using the FeTA Dataset
It is critical to quantitatively analyse the developing human fetal brai...
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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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03/16/2020
clDice – a Topology-Preserving Loss Function for Tubular Structure Segmentation
Accurate segmentation of tubular, network-like structures, such as vesse...
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10/08/2019
Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee
Fast and accurate solution of time-dependent partial differential equati...
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08/14/2019
Shape-Aware Complementary-Task Learning for Multi-Organ Segmentation
Multi-organ segmentation in whole-body computed tomography (CT) is a con...
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07/01/2019
