7 citations · 28 across the 20 of their papers we have counts for
21 papers
FedDAPL: Toward Client-Private Generalization in Federated Learning
Soroosh Safari Loaliyan, Jose-Luis Ambite, Paul M. Thompson +2
Federated Learning (FL) trains models locally at each research center or clinic and aggregates only model updates, making it a natural fit for medical imaging, where strict privacy…
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI
Nancy R. Newlin, Kurt Schilling, Serge Koudoro +33
White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (…
Synthesizing study-specific controls using generative models on open access datasets for harmonized multi-study analyses
Shruti P. Gadewar, Alyssa H. Zhu, Iyad Ba Gari +5
Neuroimaging consortia can enhance reliability and generalizability of findings by pooling data across studies to achieve larger sample sizes. To adjust for site and MRI protocol e…
Classification of Major Depressive Disorder Using Vertex-Wise Brain Sulcal Depth, Curvature, and Thickness with a Deep and a Shallow Learning Model
Roberto Goya-Maldonado, Tracy Erwin-Grabner, Ling-Li Zeng +84
Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if…
Tackling the dimensions in imaging genetics with CLUB-PLS
Andre Altmann, Ana C Lawry Aguila, Neda Jahanshad +2
A major challenge in imaging genetics and similar fields is to link high-dimensional data in one domain, e.g., genetic data, to high dimensional data in a second domain, e.g., brai…
Linking Symptom Inventories using Semantic Textual Similarity
Eamonn Kennedy, Shashank Vadlamani, Hannah M Lindsey +79
An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, resul…
A Comprehensive Corpus Callosum Segmentation Tool for Detecting Callosal Abnormalities and Genetic Associations from Multi Contrast MRIs
Shruti P. Gadewar, Elnaz Nourollahimoghadam, Ravi R. Bhatt +7
Structural alterations of the midsagittal corpus callosum (midCC) have been associated with a wide range of brain disorders. The midCC is visible on most MRI contrasts and in many…
Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures
Vladimir Belov, Tracy Erwin-Grabner, Ali Saffet Gonul +63
Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predict…
3D Grid-Attention Networks for Interpretable Age and Alzheimer's Disease Prediction from Structural MRI
Pradeep Lam, Alyssa H. Zhu, Iyad Ba Gari +2
We propose an interpretable 3D Grid-Attention deep neural network that can accurately predict a person's age and whether they have Alzheimer's disease (AD) from a structural brain…
Simultaneous Matrix Diagonalization for Structural Brain Networks Classification
Nikita Mokrov, Maxim Panov, Boris A. Gutman +3
This paper considers the problem of brain disease classification based on connectome data. A connectome is a network representation of a human brain. The typical connectome classif…
A Fast, Accurate Two-Step Linear Mixed Model for Genetic Analysis Applied to Repeat MRI Measurements
Qifan Yang, Gennady V. Roshchupkin, Wiro J. Niessen +4
Large-scale biobanks are being collected around the world in efforts to better understand human health and risk factors for disease. They often survey hundreds of thousands of indi…
Heritability estimates on resting state fMRI data using the ENIGMA analysis pipeline
Bhim M. Adhikari, Neda Jahanshad, Dinesh Shukla +8
Big data initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analysis consortium (ENIGMA), combine data collected by independent studies worldwide to achieve more…
Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification
Dmitry Petrov, Alexander Ivanov, Joshua Faskowitz +5
There is no consensus on how to construct structural brain networks from diffusion MRI. How variations in pre-processing steps affect network reliability and its ability to disting…
Classification of Major Depressive Disorder via Multi-Site Weighted LASSO Model
Dajiang Zhu, Brandalyn C. Riedel, Neda Jahanshad +13
Large-scale collaborative analysis of brain imaging data, in psychiatry and neu-rology, offers a new source of statistical power to discover features that boost ac-curacy in diseas…
Large-scale Feature Selection of Risk Genetic Factors for Alzheimer's Disease via Distributed Group Lasso Regression
Qingyang Li, Dajiang Zhu, Jie Zhang +6
Genome-wide association studies (GWAS) have achieved great success in the genetic study of Alzheimer's disease (AD). Collaborative imaging genetics studies across different researc…
A Restaurant Process Mixture Model for Connectivity Based Parcellation of the Cortex
Daniel Moyer, Boris A Gutman, Neda Jahanshad +1
One of the primary objectives of human brain mapping is the division of the cortical surface into functionally distinct regions, i.e. parcellation. While it is generally agreed tha…
Structural Connectome Validation Using Pairwise Classification
Dmitry Petrov, Boris Gutman, Alexander Ivanov +4
In this work, we study the extent to which structural connectomes and topological derivative measures are unique to individual changes within human brains. To do so, we classify st…
An Empirical Study of Continuous Connectivity Degree Sequence Equivalents
Daniel Moyer, Boris A. Gutman, Joshua Faskowitz +2
In the present work we demonstrate the use of a parcellation free connectivity model based on Poisson point processes. This model produces for each subject a continuous bivariate i…
A Continuous Model of Cortical Connectivity
Daniel Moyer, Boris A. Gutman, Joshua Faskowitz +2
We present a continuous model for structural brain connectivity based on the Poisson point process. The model treats each streamline curve in a tractography as an observed event in…
Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions
Qingyang Li, Tao Yang, Liang Zhan +6
Genome-wide association studies (GWAS) offer new opportunities to identify genetic risk factors for Alzheimer's disease (AD). Recently, collaborative efforts across different insti…
Unifying inference on brain network variations in neurological diseases: The Alzheimer's case
Daniele Durante, Madelaine Daianu, Neda Jahanshad +2
There is growing interest in understanding how the structural interconnections among brain regions change with the occurrence of neurological diseases. Diffusion weighted MRI imagi…