416 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- McGill UniversityCA39 papers
- Centre National de la Recherche ScientifiqueFR7 papers
- InsermFR6 papers
- University of PennsylvaniaUS6 papers
- Polytechnique MontréalCA5 papers
- University College LondonGB5 papers
- University of CalgaryCA5 papers
- Cornell UniversityUS4 papers
- Harvard UniversityUS4 papers
- Massachusetts General HospitalUS4 papers
- National Institutes of HealthUS4 papers
- University of British ColumbiaCA4 papers
44 papers
Comorbidity-Informed Transfer Learning for Neuro-developmental Disorder Diagnosis
Xin Wen, Shijie Guo, Wenbo Ning +4
Neuro-developmental disorders are manifested as dysfunctions in cognition, communication, behaviour and adaptability, and deep learning-based computer-aided diagnosis (CAD) can all…
Event Segmentation Applications in Large Language Model Enabled Automated Recall Assessments
Ryan A. Panela, Alex J. Barnett, Morgan D. Barense +1
Understanding how individuals perceive and recall information in their natural environments is critical to understanding potential failures in perception (e.g., sensory loss) and m…
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023
Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu +77
Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%.…
Brain states analysis of EEG predicts multiple sclerosis and mirrors disease duration and burden
István Mórocz, Mojtaba Jouzizadeh, Amir H. Ghaderi +4
Background: Any treatment of multiple sclerosis should preserve mental function, considering how cognitive deterioration interferes with quality of life. However, mental assessment…
Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge
Dominic LaBella, Ujjwal Baid, Omaditya Khanna +119
We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in…
covSTATIS: a multi-table technique for network neuroscience
Giulia Baracchini, Ju-Chi Yu, Jenny Rieck +5
Similarity analyses between multiple correlation or covariance tables constitute the cornerstone of network neuroscience. Here, we introduce covSTATIS, a versatile, linear, unsuper…
Analyzing Regional Organization of the Human Hippocampus in 3D-PLI Using Contrastive Learning and Geometric Unfolding
Alexander Oberstrass, Jordan DeKraker, Nicola Palomero-Gallagher +5
Understanding the cortical organization of the human brain requires interpretable descriptors for distinct structural and functional imaging data. 3D polarized light imaging (3D-PL…
Equivalent Time Active Cavitation Imaging
Simon Blais, Jonathan Poree, Gerardo Ramos-Palacios +4
The development of neurologically active drugs faces a challenge in treating brain diseases due to the blood-brain barrier's impermeability. High-intensity focused ultrasound can o…
A Metaheuristic for Amortized Search in High-Dimensional Parameter Spaces
Dominic Boutet, Sylvain Baillet
Parameter inference for dynamical models of (bio)physical systems remains a challenging problem. Intractable gradients, high-dimensional spaces, and non-linear model functions are…
The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)
Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff +111
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is mean…
Equivalent-Time-Active-Cavitation-Imaging Enables Vascular-Resolution Blood-Brain-Barrier-Opening-Therapy Planning
Samuel Desmarais, Gerardo Ramos-Palacios, Jonathan Poree +4
Linking cavitation and anatomy was found to be important for predictable outcomes in Focused-Ultrasound Blood-Brain-Barrier-Opening and requires high resolution cavitation mapping.…
A Tracking prior to Localization workflow for Ultrasound Localization Microscopy
Alexis Leconte, Jonathan Porée, Brice Rauby +7
Ultrasound Localization Microscopy (ULM) has proven effective in resolving microvascular structures and local mean velocities at sub-diffraction-limited scales, offering high-resol…
The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)
Maruf Adewole, Jeffrey D. Rudie, Anu Gbadamosi +48
Gliomas are the most common type of primary brain tumors. Although gliomas are relatively rare, they are among the deadliest types of cancer, with a survival rate of less than 2 ye…
Dual-encoded magnetization transfer and diffusion imaging and its application to tract-specific microstructure mapping
Ilana R Leppert, Pietro Bontempi, Christopher D Rowley +6
We present a novel dual-encoded magnetization transfer (MT) and diffusion-weighted sequence and demonstrate its potential to resolve distinct properties of white matter fiber tract…
SF2Former: Amyotrophic Lateral Sclerosis Identification From Multi-center MRI Data Using Spatial and Frequency Fusion Transformer
Rafsanjany Kushol, Collin C. Luk, Avyarthana Dey +15
Amyotrophic Lateral Sclerosis (ALS) is a complex neurodegenerative disorder involving motor neuron degeneration. Significant research has begun to establish brain magnetic resonanc…
Optimization of acquisition parameters for cortical inhomogeneous magnetization transfer (ihMT) imaging using a rapid gradient echo readout
Christopher D. Rowley, Jennifer S. W. Campbell, Ilana R. Leppert +3
Purpose: Imaging biomarkers with increased myelin specificity are needed to better understand the complex progression of neurological disorders. Inhomogeneous magnetization transfe…
High-resolution diffusion-weighted imaging at 7 Tesla: single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy
Sajjad Feizollah, Christine L. Tardif
Diffusion MRI (dMRI) is a valuable imaging technique to study the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique…
Deep radiomic signature with immune cell markers predicts the survival of glioma patients
Ahmad Chaddad, Paul Daniel Mingli Zhang, Saima Rathore +3
Imaging biomarkers offer a non-invasive way to predict the response of immunotherapy prior to treatment. In this work, we propose a novel type of deep radiomic features (DRFs) comp…
Modeling of Textures to Predict Immune Cell Status and Survival of Brain Tumour Patients
Ahmad Chaddad, Mingli Zhang, Lama Hassan +1
Radiomics has shown a capability for different types of cancers such as glioma to predict the clinical outcome. It can have a non-invasive means of evaluating the immunotherapy res…
Neuromatch Academy: Teaching Computational Neuroscience with global accessibility
Tara van Viegen, Athena Akrami, Kate Bonnen +32
Neuromatch Academy designed and ran a fully online 3-week Computational Neuroscience summer school for 1757 students with 191 teaching assistants working in virtual inverted (or fl…
Convolutional Neural Networks for cytoarchitectonic brain mapping at large scale
Christian Schiffer, Hannah Spitzer, Kai Kiwitz +6
Human brain atlases provide spatial reference systems for data characterizing brain organization at different levels, coming from different brains. Cytoarchitecture is a basic prin…
The relationship between individual variation in macroscale functional gradients and distinct aspects of ongoing thought
Brontë Mckeown, Will H. Strawson, Hao-Ting Wang +9
Contemporary accounts of ongoing thought recognise it as a heterogeneous and multidimensional construct, varying in both form and content. An emerging body of evidence demonstrates…
Local semi-supervised approach to brain tissue classification in child brain MRI
Nataliya Portman, Paule-J Toussaint, Alan C. Evans
Most segmentation methods in child brain MRI are supervised and are based on global intensity distributions of major brain structures. The successful implementation of a supervised…
Novel solutions toward high accuracy automatic brain tissue classification in young children
Nataliya Portman, Paule-J Toussaint, Alan C. Evans McConnell
Accurate automatic classification of major tissue classes and the cerebrospinal fluid in pediatric MR scans of early childhood brains remains a challenge. A poor and highly variabl…