{"id":3014,"date":"2025-10-12T23:41:57","date_gmt":"2025-10-12T21:41:57","guid":{"rendered":"https:\/\/portale2.unime.it\/ai-healthlab\/?p=3014"},"modified":"2025-10-15T12:27:57","modified_gmt":"2025-10-15T10:27:57","slug":"neurodegenerative-disease-progression-modeling","status":"publish","type":"post","link":"https:\/\/portale2.unime.it\/ai-healthlab\/en\/neurodegenerative-disease-progression-modeling\/","title":{"rendered":"Neurodegenerative Disease Progression Modeling"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"3014\" class=\"elementor elementor-3014\">\n\t\t\t\t<div class=\"elementor-element elementor-element-36913dd3 e-flex e-con-boxed e-con e-parent\" data-id=\"36913dd3\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-799439cb elementor-widget elementor-widget-text-editor\" data-id=\"799439cb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Understanding and predicting the progression of neurodegenerative diseases are central topics in modern neurological research. My scientific production includes a series of innovative and validated models\u2014ranging from the pioneering DANI-Net and 4D-DANI-Net to the most recent BrLP, TADM, and their extensions\u2014recognized and awarded by leading conferences and international journals.<\/p>\n<p><b>Motivations &amp; Objectives<\/b><\/p>\n<ul>\n<li>Simulate and predict the individual progression of neurodegeneration on longitudinal MRI data.<\/li>\n<li>Improve precision medicine by providing customizable and validated clinical tools.<\/li>\n<li>Bring generative and diffusion models from experimental research to large-scale application.<\/li>\n<\/ul>\n<p><b>Methods<\/b><\/p>\n<ul>\n<li>DANI-Net\/4D-DANI-Net: Adversarial networks capable of generating realistic simulations of brain pathological progression based on longitudinal MRI.<\/li>\n<li>BrLP: Spatiotemporal latent diffusion model, enhanced by prior clinical knowledge infusion, predictive consistency stabilization (LAS), and training on over 11,000 MRIs from ADNI, OASIS, AIBL.<\/li>\n<li>TADM: Diffusion-based model aimed at explicit temporal modeling of degenerative brain progression, with extensions including bidirectional temporal regularizations (TADM-3D\/BiTR, arXiv 2025).<\/li>\n<li>Technical assessment on SPIE: Systematic study on comparative performance of different diffusion approaches for Alzheimer&#8217;s progression.<\/li>\n<\/ul>\n<p><b>Results &amp; Impact<\/b><\/p>\n<ul>\n<li>Significant increases in volumetric accuracy and clinical prediction compared to previous state-of-the-art.<\/li>\n<li>Awards and recognition at MICCAI, MedIA, SPIE (Best Paper nomination, Runner-up, extended publication on MedIA).<\/li>\n<li>Open-source codes and pipelines ready for reproducible testing and future applications (see repositories below).<\/li>\n<\/ul>\n<h3><br><\/h3><h3>Related Scientific Articles<\/h3>\n<ul>\n<li>DANI-Net (MICCAI 2019):<br><a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-030-32248-9_19\">Degenerative adversarial neuroimage nets: generating images that mimic disease progression<\/a><br>Authors: Daniele Ravi, Daniel C Alexander, Neil P Oxtoby, Alzheimer\u2019s Disease Neuroimaging Initiative<\/li>\n<li>4D-DANI-Net (MedIA 2022):<br><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1361841521003029\">Degenerative adversarial neuroimage nets for brain scan simulations: Application in ageing and dementia<\/a><br>Authors: Daniele Ravi, Stefano B Blumberg, Silvia Ingala, Frederik Barkhof, Daniel C Alexander, Neil P Oxtoby, Alzheimer\u2019s Disease Neuroimaging Initiative<\/li>\n<li>BrLP (MICCAI 2024 \u2013 Best Paper Nomination):<br><a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-72069-7_17\">Enhancing spatiotemporal disease progression models via latent diffusion and prior knowledge<\/a><br>Authors: Lemuel Puglisi, Daniel C Alexander, Daniele Rav\u00ec<\/li>\n<li>BrLP \u2013 Extended Version (MedIA 2025):<br><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1361841525002816\">Brain latent progression: Individual-based spatiotemporal disease progression on 3D brain MRIs via latent diffusion<\/a><br>Authors: Lemuel Puglisi, Daniel C Alexander, Daniele Rav\u00ec, Alzheimer\u2019s Disease Neuroimaging Initiative<\/li>\n<li>TADM (MICCAI 2024):<br><a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-72069-7_42\">Tadm: Temporally-aware diffusion model for neurodegenerative progression on brain MRI<\/a><br>Authors: Mattia Litrico, Francesco Guarnera, Mario Valerio Giuffrida, Daniele Rav\u00ec, Sebastiano Battiato<\/li>\n<li>TADM-3D with BiTR (arXiv 2025):<br><a href=\"https:\/\/arxiv.org\/abs\/2509.03141\">Temporally-Aware Diffusion Model for Brain Progression Modelling with Bidirectional Temporal Regularisation<\/a><br>Authors: Mattia Litrico, Francesco Guarnera, Mario Valerio Giuffrida, Daniele Rav\u00ec, Sebastiano Battiato<\/li>\n<li>Assessment on SPIE (2025):<br><a href=\"https:\/\/scholar.google.com\/citations?view_op=view_citation&amp;hl=it&amp;user=qh2Rr-cAAAAJ&amp;cstart=20&amp;pagesize=80&amp;citation_for_view=qh2Rr-cAAAAJ:dshw04ExmUIC\">A technical assessment of latent diffusion for Alzheimer\u2019s disease progression<\/a><br>Authors: E McMaster, L Puglisi, C Gao, AR Krishnan, AM Saunders, D Ravi, T Vercauteren, DC Alexander, NP Oxtoby, Alzheimer\u2019s Disease Neuroimaging Initiative<\/li>\n<\/ul>\n<h3><br><\/h3><h3>Code Repositories<\/h3>\n<ul>\n<li>BrLP: <a href=\"https:\/\/github.com\/LemuelPuglisi\/BrLP\">LemuelPuglisi\/BrLP<\/a> (core: <code>src\/brlp\/<\/code>)<\/li>\n<li>DANI-Net &amp; 4D-DANI-Net: <a href=\"https:\/\/github.com\/daniravi\/Brain-MRI-Simulator\">daniravi\/Brain-MRI-Simulator<\/a> (implementations for progression, aging, and simulation)<\/li>\n<\/ul>\n<h3><br><\/h3><h3>Team &amp; Authors<\/h3>\n<ul>\n<li><a href=\"https:\/\/github.com\/daniravi\">Daniele Rav\u00ec<\/a> (PI, design, supervision of DANI-Net, 4D-DANI-Net, BrLP, TADM models)<\/li>\n<li><a href=\"https:\/\/github.com\/LemuelPuglisi\">Lemuel Puglisi<\/a> (First author BrLP)<\/li>\n<li>Daniel C. Alexander, Neil P. Oxtoby, Stefano B. Blumberg, Silvia Ingala, Mattia Litrico, Francesco Guarnera, Mario Valerio Giuffrida, Sebastiano Battiato, Frederik Barkhof, E McMaster, AR Krishnan, AM Saunders, T Vercauteren, Alzheimer\u2019s Disease Neuroimaging Initiative<\/li>\n<\/ul>\n<p>Best Paper Nomination @MICCAI &amp; MedIA.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-caa0f17 elementor-widget elementor-widget-video\" data-id=\"caa0f17\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/youtu.be\\\/6YKz2MNM4jg&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Understanding and predicting the progression of neurodegenerative diseases are central topics in modern neurological research. My scientific production includes a series of innovative and validated models\u2014ranging from the pioneering DANI-Net and 4D-DANI-Net to the most recent BrLP, TADM, and their extensions\u2014recognized and awarded by leading conferences and international journals. Motivations &amp; Objectives Simulate and predict&hellip; <a class=\"more-link\" href=\"https:\/\/portale2.unime.it\/ai-healthlab\/en\/neurodegenerative-disease-progression-modeling\/\">Continua a leggere <span class=\"screen-reader-text\">Neurodegenerative Disease Progression Modeling<\/span><\/a><\/p>\n","protected":false},"author":94,"featured_media":2123,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34],"tags":[9,11],"class_list":["post-3014","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-eng-en","tag-formazione-en","tag-ricerca-en","entry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Neurodegenerative Disease Progression Modeling - AI-HealthLab<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/portale2.unime.it\/ai-healthlab\/en\/neurodegenerative-disease-progression-modeling\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Neurodegenerative Disease Progression Modeling - AI-HealthLab\" \/>\n<meta property=\"og:description\" content=\"Understanding and predicting the progression of neurodegenerative diseases are central topics in modern neurological research. My scientific production includes a series of innovative and validated models\u2014ranging from the pioneering DANI-Net and 4D-DANI-Net to the most recent BrLP, TADM, and their extensions\u2014recognized and awarded by leading conferences and international journals. 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