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08/06/2023
Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical Neuroscience
Machine learning (ML) has shown great promise for revolutionizing a numb...
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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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09/27/2022
Deep Learning Based Detection of Enlarged Perivascular Spaces on Brain MRI
Deep learning has been demonstrated effective in many neuroimaging appli...
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05/26/2022
Machine Learning Models Are Not Necessarily Biased When Constructed Properly: Evidence from Neuroimaging Studies
Despite the great promise that machine learning has offered in many fiel...
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02/22/2022
Robust Hierarchical Patterns for identifying MDD patients: A Multisite Study
Many supervised machine learning frameworks have been proposed for disea...
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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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09/08/2021
Disentangling Alzheimer's disease neurodegeneration from typical brain aging using machine learning
Neuroimaging biomarkers that distinguish between typical brain aging and...
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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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06/12/2021
Harmonization with Flow-based Causal Inference
Heterogeneity in medical data, e.g., from data collected at different si...
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06/10/2021
Ensemble inversion for brain tumor growth models with mass effect
We propose a method for extracting physics-based biomarkers from a singl...
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05/13/2021
Learning Robust Hierarchical Patterns of Human Brain across Many fMRI Studies
Resting-state fMRI has been shown to provide surrogate biomarkers for th...
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05/12/2021
The Federated Tumor Segmentation (FeTS) Challenge
This manuscript describes the first challenge on Federated Learning, nam...
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04/20/2021
Extraction of Hierarchical Functional Connectivity Components in human brain using Adversarial Learning
The estimation of sparse hierarchical components reflecting patterns of ...
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03/23/2021
Embracing the Disharmony in Heterogeneous Medical Data
Heterogeneity in medical imaging data is often tackled, in the context o...
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10/11/2020
Medical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging
Conventional and deep learning-based methods have shown great potential ...
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08/17/2020
A Deep Network for Joint Registration and Reconstruction of Images with Pathologies
Registration of images with pathologies is challenging due to tissue app...
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02/09/2020
The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up
We present the findings of "The Alzheimer's Disease Prediction Of Longit...
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07/03/2019
DeepMRSeg: A convolutional deep neural network for anatomy and abnormality segmentation on MR images
Segmentation has been a major task in neuroimaging. A large number of au...
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06/19/2019
Extraction of hierarchical functional connectivity components in human brain using resting-state fMRI
The study of hierarchy in networks of the human brain has been of signif...
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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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08/13/2018
CLAIRE: A distributed-memory solver for constrained large deformation diffeomorphic image registration
We introduce CLAIRE, a distributed-memory algorithm and software for sol...
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07/02/2018
Generative discriminative models for multivariate inference and statistical mapping in medical imaging
This paper presents a general framework for obtaining interpretable mult...
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02/28/2018