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08/31/2023
Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images
Multiple Sclerosis (MS) is a severe neurological disease characterized b...
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08/26/2023
Bias in Unsupervised Anomaly Detection in Brain MRI
Unsupervised anomaly detection methods offer a promising and flexible al...
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08/18/2023
Denoising diffusion-based MR to CT image translation enables whole spine vertebral segmentation in 2D and 3D without manual annotations
Background: Automated segmentation of spinal MR images plays a vital rol...
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08/01/2023
Metrics to Quantify Global Consistency in Synthetic Medical Images
Image synthesis is increasingly being adopted in medical image processin...
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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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06/28/2023
Inter-Rater Uncertainty Quantification in Medical Image Segmentation via Rater-Specific Bayesian Neural Networks
Automated medical image segmentation inherently involves a certain degre...
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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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03/27/2023
Multi-contrast MRI Super-resolution via Implicit Neural Representations
Clinical routine and retrospective cohorts commonly include multi-parame...
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03/21/2023
Semantic Latent Space Regression of Diffusion Autoencoders for Vertebral Fracture Grading
Vertebral fractures are a consequence of osteoporosis, with significant ...
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03/15/2023
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection
Early and accurate disease detection is crucial for patient management a...
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01/18/2023
ViT-AE++: Improving Vision Transformer Autoencoder for Self-supervised Medical Image Representations
Self-supervised learning has attracted increasing attention as it learns...
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12/31/2022
Approaching Peak Ground Truth
Machine learning models are typically evaluated by computing similarity ...
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12/03/2022
A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images
Quantifying the perceptual similarity of two images is a long-standing p...
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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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03/30/2022
Interpretable Vertebral Fracture Diagnosis
Do black-box neural network models learn clinically relevant features fo...
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02/08/2022
On the Pitfalls of Using the Residual Error as Anomaly Score
Many current state-of-the-art methods for anomaly localization in medica...
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12/13/2021
The Brain Tumor Sequence Registration Challenge: Establishing Correspondence between Pre-Operative and Follow-up MRI scans of diffuse glioma patients
Registration of longitudinal brain Magnetic Resonance Imaging (MRI) scan...
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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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07/05/2021
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly ...
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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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03/05/2021
FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation
In recent years, data-driven machine learning (ML) methods have revoluti...
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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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06/23/2020
Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI
Brain pathologies can vary greatly in size and shape, ranging from few p...
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04/07/2020
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study
Deep unsupervised representation learning has recently led to new approa...
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03/18/2020
Train, Learn, Expand, Repeat
High-quality labeled data is essential to successfully train supervised ...
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01/25/2020
e-UDA: Efficient Unsupervised Domain Adaptation for Cross-Site Medical Image Segmentation
Domain adaptation in healthcare data is a potentially critical component...
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04/29/2019
DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis
Recent studies on medical image synthesis reported promising results usi...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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07/02/2018
Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans and Bayesian Inference
Glioblastoma is a highly invasive brain tumor, whose cells infiltrate su...
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07/02/2018
Personalized Radiotherapy Design for Glioblastoma Using Mathematical Models, Multimodal Scans and Bayesian Inference
Glioblastoma is a highly invasive brain tumor, whose cells infiltrate su...
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07/02/2018
Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration
Existing radiotherapy (RT) plans for brain tumors derive from population...
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04/12/2018