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Paul M Thompson

Explore the profile of Paul M Thompson including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 1173
Citations 47097
Followers 0
Related Specialties
Neurology
Psychiatry
Radiology
Top 10 Co-Authors
Neda Jahanshad
Arthur W Toga
Margaret J Wright
Sophia I Thomopoulos
Greig I de Zubicaray
Katie L McMahon
Dan J Stein
Nicholas G Martin
Clifford R Jack Jr
Michael W Weiner
Published In
Neuroimage
Hum Brain Mapp
Proc IEEE Int Symp Biomed Imaging
Neurobiol Aging
Med Image Comput Comput Assist Interv
Affiliations
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Recent Articles
1.
Synthetic Diffusion Tensor Imaging Maps Generated by 2D and 3D Probabilistic Diffusion Models: Evaluation and Applications
Chattopadhyay T, Jagad C, Kush R, Desai V, Thomopoulos S, Villalon-Reina J, et al.
bioRxiv . 2025 Mar; PMID: 40060678
Diffusion tensor imaging (DTI) is a key neuroimaging modality for assessing brain tissue microstructure, yet high-quality acquisitions are costly, time-intensive, and prone to artifacts. To address data scarcity and privacy...
2.
Bundle Analytics based Data Harmonization for Multi-Site Diffusion MRI Tractometry
Chandio B, Villalon-Reina J, Nir T, Thomopoulos S, Feng Y, Benavidez S, et al.
Annu Int Conf IEEE Eng Med Biol Soc . 2025 Mar; 2024:1-7. PMID: 40039717
The neural pathways of the living human brain can be tracked using diffusion MRI-based tractometry. Along-tract statistical analysis of microstructural metrics can reveal the effects of neurological and psychiatric diseases...
3.
Counterfactual MRI Generation with Denoising Diffusion Models for Interpretable Alzheimer's Disease Effect Detection
Dhinagar N, Thomopoulos S, Laltoo E, Thompson P
Annu Int Conf IEEE Eng Med Biol Soc . 2025 Mar; 2024:1-6. PMID: 40039528
Generative AI models have recently achieved mainstream attention with the advent of powerful approaches such as SORA, DALL-E and stable diffusion. The underlying breakthrough generative mechanism of denoising diffusion modeling...
4.
Deep Normative Tractometry for Identifying Joint White Matter Macro- and Micro-structural Abnormalities in Alzheimer's Disease
Feng Y, Chandio B, Villalon-Reina J, Benavidez S, Chattopadhyay T, Chehrzadeh S, et al.
Annu Int Conf IEEE Eng Med Biol Soc . 2025 Mar; 2024:1-7. PMID: 40039444
This study introduces the Deep Normative Tractometry (DNT) framework, that encodes the joint distribution of both macrostructural and microstructural profiles of the brain white matter tracts through a variational autoencoder...
5.
Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models
Benavidez S, Abaryan Z, Kim G, Laltoo E, McCracken J, Thompson P, et al.
Annu Int Conf IEEE Eng Med Biol Soc . 2025 Mar; 2024:1-7. PMID: 40039411
Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical...
6.
Brain Age Analysis and Dementia Classification using Convolutional Neural Networks trained on Diffusion MRI: Tests in Indian and North American Cohorts
Chattopadhyay T, Joshy N, Ozarkar S, Buwa K, Feng Y, Laltoo E, et al.
Annu Int Conf IEEE Eng Med Biol Soc . 2025 Mar; 2024:1-7. PMID: 40039079
Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzheimer's disease or infer dementia severity from T1-weighted brain MRI scans. Here, we examine the value...
7.
Parameter Efficient Fine-tuning of Transformer-based Masked Autoencoder Enhances Resource Constrained Neuroimage Analysis
Dhinagar N, Ozarkar S, Buwa K, Thomopoulos S, Owens-Walton C, Laltoo E, et al.
bioRxiv . 2025 Mar; PMID: 40027656
Recent innovations in artificial intelligence (AI) have increasingly focused on large-scale foundational models that are more general purpose in contrast to conventional models trained to perform specialized tasks. Transformer-based architectures...
8.
Leveraging a Vision-Language Model with Natural Text Supervision for MRI Retrieval, Captioning, Classification, and Visual Question Answering
Dhinagar N, Thomopoulos S, Thompson P
bioRxiv . 2025 Mar; PMID: 40027630
Clinical Relevance: By learning a cross-modal embedding of radiologic features and text, our approach can learn to perform diagnostic and prognostic assessments in AD research as well as to assist...
9.
Estimating Multimodal Structural Brain Variability in Schizophrenia Spectrum Disorders: A Worldwide ENIGMA Study
Omlor W, Rabe F, Fuchs S, Surbeck W, Cecere G, Huang G, et al.
Am J Psychiatry . 2025 Feb; :appiajp20230806. PMID: 40007253
Objective: The clinical diversity of schizophrenia is reflected by structural brain variability. It remains unclear how this variability manifests across different gray and white matter features. In this meta- and...
10.
Development and validation of a machine learning model to predict cognitive behavioral therapy outcome in obsessive-compulsive disorder using clinical and neuroimaging data
van de Mortel L, Bruin W, Alonso P, Bertolin S, Feusner J, Guo J, et al.
medRxiv . 2025 Feb; PMID: 39990555
Cognitive behavioral therapy (CBT) is a first-line treatment for obsessive-compulsive disorder (OCD), but clinical response is difficult to predict. In this study, we aimed to develop predictive models using clinical...