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06/19/2023
A Lightweight Causal Model for Interpretable Subject-level Prediction
Recent years have seen a growing interest in methods for predicting a va...
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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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07/10/2022
An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation
In this paper we describe and validate a longitudinal method for whole-b...
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09/25/2021
Prediction of MGMT Methylation Status of Glioblastoma using Radiomics and Latent Space Shape Features
In this paper we propose a method for predicting the status of MGMT prom...
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09/25/2021
Predicting survival of glioblastoma from automatic whole-brain and tumor segmentation of MR images
Survival prediction models can potentially be used to guide treatment of...
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07/20/2021
SynthSeg: Domain Randomisation for Segmentation of Brain MRI Scans of any Contrast and Resolution
Despite advances in data augmentation and transfer learning, convolution...
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03/23/2021
An augmentation strategy to mimic multi-scanner variability in MRI
Most publicly available brain MRI datasets are very homogeneous in terms...
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09/11/2020
3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology
Neuroimaging to neuropathology correlation (NTNC) promises to enable the...
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08/12/2020
A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis
In this paper we propose a novel method for the segmentation of longitud...
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05/11/2020
A Contrast-Adaptive Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis
Here we present a method for the simultaneous segmentation of white matt...
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03/04/2020
A Learning Strategy for Contrast-agnostic MRI Segmentation
We present a deep learning strategy that enables, for the first time, co...
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11/08/2019
Relevance Vector Machines for harmonization of MRI brain volumes using image descriptors
With the increased need for multi-center magnetic resonance imaging stud...
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10/10/2019
Semi-Supervised Variational Autoencoder for Survival Prediction
In this paper we propose a semi-supervised variational autoencoder for c...
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03/11/2019
Joint inference on structural and diffusion MRI for sequence-adaptive Bayesian segmentation of thalamic nuclei with probabilistic atlases
Segmentation of structural and diffusion MRI (sMRI/dMRI) is usually perf...
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01/17/2019
PSACNN: Pulse Sequence Adaptive Fast Whole Brain Segmentation
With the advent of convolutional neural networks (CNN), supervised learn...
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01/17/2019
PSACNN: Pulse Sequence Resilient Fast Whole Brain Segmentation
With the advent of convolutional neural networks (CNN), supervised learn...
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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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07/18/2018
A Modality-Adaptive Method for Segmenting Brain Tumors and Organs-at-Risk in Radiation Therapy Planning
In this paper we present a method for simultaneously segmenting brain tu...
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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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06/22/2018