I indicate in green the publications in which I was last author, in red the publications as first author, and
in blue the
publications in which I gave a significant contribution as either second or
second-last author.
Naming convention:
j = journal, c = conference, w =
workshop, b = book, p/o = poster/oral presentation at clinical conference, s =
submitted
ml = machine learning, mi = medical
imaging, cl = clinical
Machine Learning journals (2)
[j.ml1]
Yann Fraboni, Richard Vidal, Laetitia Kameni and Marco Lorenzi. A general theory for federated optimization with asynchronous and
heterogeneous clients updates. Journal of Machine Learning Research, 24 (110), 1-43 [link]
[j.ml2] Etrit Haxholli and Marco Lorenzi. On Tail Decay
Rate Estimation of Loss Function
Distributions. Journal of Machine Learning Research. To appear. [link]
Medical Imaging and
Computer Vision journals (22)
[j.mi1] Riccardo Taiello, Melek Önen, Francesco Capano, Olivier
Humbert and Marco Lorenzi. Privacy Preserving Image Registration. Medical Image Analysis preprint 2024.
[j.mi2] Gerard
Martí-Juan, Marco Lorenzi, Gemma Piella. MC-RVAE: Multi-channel recurrent variational
autoencoder for multimodal Alzheimer’s disease progression modelling. NeuroImage: 119892, 2023. [link]
[j.mi3] Marie Deprez, Julien
Moreira, Maxime Sermesant, Marco Lorenzi.
Decoding genetic markers of multiple phenotypic layers through biologically
constrained Genome-to-Phenome Bayesian Sparse Regression. Frontiers in
Molecular Medicine, 2, 830956. [link]
[j.mi4]
Irene Balelli, Santiago Silva, and Marco Lorenzi. A Differentially Private Probabilistic
Framework for Modeling the Variability Across
Federated Datasets of Heterogeneous Multi-View Observations. Journal of
Machine Learning for Biomedical Imaging, 2022. [link]
[j.mi5] Sara Garbarino and Marco Lorenzi. Investigating hypotheses of neurodegeneration
by learning dynamical systems of protein propagation in the brain. NeuroImage, 235, 117980, 2021. [link]
[j.mi6] Vien Ngoc Dang, Francesco Galati, Rosa Cortese, Giuseppe Di Giacomo, Viola Marconetto, Prateek Mathur, Karim Lekadir,
Marco Lorenzi, Ferran Prados, Maria A Zuluaga. Vessel–CAPTCHA: an efficient learning framework
for vessel annotation and segmentation. Medical Image Analysis, 75:102263, Elsevier, 2021. [link]
[j.mi7] Adrià Casamitjana, Marco Lorenzi, Sebastiano Ferraris, Loïc
Peter, Marc Modat, Allison Stevens, Bruce Fischl, Tom Vercauteren, Juan
Eugenio Iglesias. Robust joint registration of multiple stains and MRI for
multimodal 3D histology reconstruction: Application to the Allen human brain
atlas. Medical
Image Analysis, 75:102265, 2021. [link]
[j.mi8] Jaume Banus,
Marco Lorenzi, Oscar Camara, Maxime Sermesant.
Biophysics–based statistical learning: Application to heart and brain
interactions. Medical Image Analysis, 72:102089, Elsevier, 2021. [link]
[j.mi9] Georgios Lazaridis, Marco Lorenzi, Sebastien Ourselin, and David Garway-Heath.
Improving statistical power of glaucoma clinical trials using an ensemble of
cyclical generative adversarial networks. Medical Image
Analysis, 68:101906, 2021. [link]
[j.mi10] Clément Abi Nader, Nicholas Ayache,
Philippe Robert and Marco Lorenzi. Monotonic
Gaussian Process for spatio-temporal disease
progression modeling in brain imaging data. NeuroImage, 205:15, 116266, 2020. [link]
[j.mi11] Raphael Sivera, Hervé Delingette, Marco Lorenzi, Xavier Pennec, Nicholas Ayache. A model of brain morphological changes related
to aging and Alzheimer's disease from cross-sectional assessments. NeuroImage. 198:255-270, 2019. [link]
[j.mi12] Claire Cury, Stanley Durrleman, David Cash, Marco Lorenzi, Jennifer Nicholas, et al. Spatiotemporal
Analysis for Detection of Pre-symptomatic Shape Changes in Neurodegenerative
diseases: applied to GENFI study. NeuroImage, 188, 282-290, 2019. [link]
[j.mi13] Sebastiano Ferraris, Hannes van der Merle, Lennart
Van Der Veeken, Herran Prados, Juan Eugenio Iglesias, Andrew Melbourne, Marco Lorenzi, Marc Modat, Willy Gsell, Jan Deprest, Tom Vercauteren. A magnetic resonance multi-atlas for the
neonatal rabbit brain. NeuroImage, 179, 187-198, 2018. [link]
[j.mi14] Marco Lorenzi, Maurizio Filippone, Giovanni B. Frisoni,
Daniel C. Alexander, Sebastien Ourselin. Probabilistic
disease progression modeling to characterize
diagnostic uncertainty: application to staging and prediction in Alzheimer's
disease. NeuroImage,
S1053-8119(17)30706-1, 2017. [link]
[j.mi15] Alex F. Mendelson, Maria A. Zuluaga,
Marco Lorenzi, Brian
F. Hutton, Sebastien Ourselin. Selection bias in
the reported performances of AD classification pipelines. NeuroImage: Clinical, 14, 400-416, 2017. [link]
[j.mi16] Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, Xavier Pennec. A biophysical model of brain deformation to
simulate and analyze longitudinal MRIs of patients
with Alzheimer's disease. NeuroImage, 134, 35-52, 2017. [link]
[j.mi17] Mehdi Hadj-Hamou, Marco Lorenzi, Nicholas Ayache, Xavier Pennec.
Longitudinal analysis of image time series with diffeomorphic deformations: a
computational framework based on stationary velocity fields. Frontiers in
Neuroscience, 10, 236, 2016. [link]
[j.mi18] David M. Cash, Chris Frost, Leonardo O. Iheme, Devrim Unay, Melek
Kandemir, Jurgen Fripp,
Olivier Salvado, Pierrick Bourgeat, Martin Reuter, Bruce Fischl,
Marco Lorenzi,
Giovanni B. Frisoni, Xavier Pennec,
Ronald K. Pierson, et al. Assessing atrophy measurement techniques in
dementia: Results from the MIRIAD atrophy challenge. NeuroImage, 123: 149-164, 2015. [link]
[j.mi19] Marco Lorenzi, Nicholas Ayache and Xavier Pennec. Regional
Flux analysis for discovering and quantifying anatomical changes: An
application to the brain morphometry in Alzheimer's disease. NeuroImage, 115:224-234, 2015. [link]
[j.mi20]
Marco Lorenzi and Xavier Pennec. Efficient
Parallel Transport of Deformations in Time Series of Images: from Schild's to Pole Ladder. Journal of Mathematical
Imaging and Vision, 50(1-2):5-17, 2014. [link]
[j.mi21] Marco Lorenzi, Nicholas Ayache, Giovanni B. Frisoni, and
Xavier Pennec. LCC-Demons: a robust and accurate
symmetric diffeomorphic registration algorithm. NeuroImage, 81(1):470-483, 2013.
[link]
[j.mi22]
Marco Lorenzi and Xavier Pennec. Geodesics,
Parallel Transport & One-parameter Subgroups for Diffeomorphic Image Registration.
International Journal of Computer Vision, 105(2):111-127,
2013. [link]
Clinical journals
(18)
[j.cl1]
Clement Abi Nader, Federica Ribaldi, Giovanni B. Frisoni, Valentina Garibotto,
Philippe Robert, Nicholas Ayache, and Marco Lorenzi. SimulAD: a
dynamical model for personalized simulation and disease staging in Alzheimer’s
disease. Neurobiology of Aging 113: 73-83, 2022. [link]
[j.cl2] Georgios Lazaridis, Giovanni Montesano, Saman
Sadeghi Afgeh, Jibran
Mohamed-Noriega, Sebastien Ourselin, Marco Lorenzi, and David F. Garway-Heath.
Predicting visual fields from optical coherence tomography via an ensemble
of deep representation learners. American journal of ophthalmology 238:
52-65, 2022. [link]
[j.cl3] Andres Diaz-Pinto, Nishant Ravikumar, Rahman Attar, Avan Suinesiaputra, Yitian Zhao, Eylem Levelt, Erica Dall’Armellina, Marco
Lorenzi, Qingyu Chen, Tiarnan
D. L. Keenan, Elvira Agrón, Emily Y. Chew, Zhiyong Lu, Chris P. Gale, Richard P. Gale, Sven Plein
& Alejandro F. Frangi. Predicting myocardial
infarction through retinal scans and minimal personal information. Nature Machine Intelligence 4, no. 1: 55-61, 2022. [link]
[j.cl4] Giorgos
Lazaridis, Marco Lorenzi, Jibran
Mohamed-Noriega, Soledad Aguilar-Munoa, Katsuyoshi Suzuki, Hiroki Nomoto,
Sebastien Ourselin, David F. Garway-Heath.
OCT signal enhancement with deep learning. Ophthalmology Glaucoma, 4(3),
295-304, 2021. [link]
[j.cl5] Clément Abi Nader, Nicholas Ayache, Giovanni Frisoni,
Philippe Robert, Marco Lorenzi. Simulating the
outcome of amyloid treatments in Alzheimer's Disease from multi–modal imaging
and clinical data. Brain Communications, Oxford University
Press, 2021. [link]
[j.cl6]
Peter A. Wijeratne, Sara Garbarino, Sarah Gregory, Eileanoir B. Johnson, Rachael I. Scahill,
Jane S. Paulsen, Sarah J. Tabrizi, Marco Lorenzi, and Daniel C.
Alexander. Revealing the timeline of structural MRI changes in premanifest
to manifest Huntington disease. Neurology Genetics 7:5, 2021. [link]
[j.cl7] Raphaël Sivera, Nicolas
Capet, Valeria Manera, Roxane Fabre, Marco Lorenzi, Hervé Delingette, Xavier Pennec,
Nicholas Ayache, Philippe Robert. Voxel–based
assessments of treatment effects on longitudinal brain changes in the
Multidomain Alzheimer Preventive Trial cohort. Neurobiology of Aging,
Elsevier, 94, 50–59, 2020. [link]
[j.cl8]
Sara Garbarino, Marco Lorenzi, Neil P Oxtoby,
Elisabeth J Vinke, Razvan V Marinescu, Arman Eshaghi, M Arfan Ikram, Wiro J Niessen, Olga Ciccarelli,
Frederik Barkhof, Jonathan M Schott, Meike W Vernooij, Daniel C
Alexander. Differences in topological progression profile among
neurodegenerative diseases from imaging data, Elife, 8, e49298, 2019. [link]
[j.cl9] Marzia A Scelsi, Raiyan R Khan, Marco
Lorenzi, Leigh Christopher, Michael D Greicius,
Jonathan M Schott, Sebastien Ourselin, Andre Altmann.
Genetic study of multimodal imaging Alzheimer’s disease progression score
implicates novel loci. Brain, Volume 141, Issue 7:1, 2167–2180, 2018 [link]
[j.cl10]
Marco Lorenzi, Andre Altmann, Boris Gutman, Selina Wray, Charles
Arber, Derrek P. Hibar, Neda Jahanshad,
Jonathan M. Schott, Daniel C. Alexander, Paul M. Thompson and Sebastien Ourselin. Susceptibility of brain atrophy to TRIB3 in
Alzheimer's disease: Evidence from functional prioritization in imaging
genetics. Proceedings of the National Academy of Sciences
of the United States of America (PNAS). 115 (12) 3162-3167, 2018. [link]
[j.cl11] Marco Lorenzi, Ivor J. Simpson,
Alex F. Mendelson, Sjoerd B. Vos, M. Jorge Cardoso,
Marc Modat, Jonathan Schott, Sebastien Ourselin. Multimodal Image Analysis in Alzheimer's
Disease via Statistical Modelling of Non-local Intensity Correlations.
Scientific Reports (NPG), 6, 2261, 2016. [link]
[j.cl12] Marco Lorenzi, Xavier Pennec, Giovanni B. Frisoni and
Nicholas Ayache. Disentangling Normal Aging from
Alzheimer's Disease in Structural MR Images. Neurobiology of Aging, 36:S42-S52, 2015. [link]
[j.cl13] Antonello Preti, Cristina Muscio, Marina Boccardi, M Marco Lorenzi, Giovanni de Girolamo, Giovanni B. Frisoni. Impact of alcohol consumption in healthy
adults: A magnetic resonance imaging investigation. Psychiatry Research:
Neuroimaging, 224 (2), 96-103, 2014. [link]
[j.cl14] Roberta Rossi, Michela Pievani,
Marco Lorenzi, Marina Boccardi, Rossella Beneduce, Stefano Bignotti, Genoveffa Borsci, Maria Cotelli, Panteleimon Giannakopoulos, Laura R. Magni, Luciana Rillosi, Sandra Rosini, Giuseppe Rossi, and Giovanni B. Frisoni.
Structural brain features of borderline personality and bipolar disorders.
Psychiatry Research: Neuroimaging, 213(2):83-91, 2013. [link]
[j.cl15]
Marco Lorenzi, Alberto Beltramello,
Nicola Mercuri, Elisa Canu,
Giada Zoccatelli, Francesca Pizzini,
Franco Alessandrini, Maria Cotelli,
Sandra Rosini, Daniela Costardi,
Carlo Caltagirone, and Giovanni B. Frisoni. Effect of memantine on resting state default
mode network activity in Alzheimer's disease. Drugs and Aging,
28(3):205-217, 2011. [link]
[j.cl16]
Marco Lorenzi, Michael Donohue, Donata Paternico, Cristina Scarpazza,
Susanne Ostrowitzki, Olivier Blin, Elaine Irving, and
Giovanni B. Frisoni. Enrichment through biomarkers
in clinical trials of Alzheimer's drugs in patients with mild cognitive
impairment. Neurobiology of Aging, 31(8):1443-1451, 2010. [link]
[j.cl17] Anna Caroli, Marco Lorenzi, Cristina Geroldi, Flavio
Nobili, Barbara Paghera, Mario Bonetti, Maria Cotelli, Giovanni B. Frisoni. Metabolic
compensation and depression in Alzheimer's disease. Dementia and geriatric
cognitive disorders, 29(1):37-45, 2010. [link]
[j.cl18] Giovanni B. Frisoni,
Marco Lorenzi, Anna Caroli, Nina Kemppainen,
Kjell Nagren, and Juha O. Rinne. In vivo mapping of amyloid toxicity in
Alzheimer's disease. Neurology, 72(17): 1504-1511, 2009. [link]
Highly selective machine learning conferences (7) (acceptance rate ~25%)
[c.ml1] Yann Fraboni,
Martin Van Waerbeke, Richard Vidal, Laetitia Kameni and Marco Lorenzi. Sequential
Informed Federated Unlearning: Efficient and Provable Client Unlearning in
Federated Optimization. 27th International Conference on Artificial
Intelligence and Statistics, AISTATS, 2024. [link]
[c.ml2]
Jean Ogier Du Terrail,
Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy
Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec,
Constantin Philippenko, Santiago Silva, Maria Teleńczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi,
Giovanni Neglia, Marc Tommasi,
Mathieu Andreux. FLamby: Datasets and Benchmarks for
Cross-Silo Federated Learning in Realistic Healthcare Settings. In NeurIPS, Datasets and Benchmarks Track. 2022. [link]
[c.ml3]
Yann Fraboni, Richard Vidal, Laetitia Kameni, and Marco Lorenzi. A General Theory
for Client Sampling in Federated Learning. In International Workshop on
Trustworthy Federated Learning in Conjunction with IJCAI (FL-IJCAI'22). 2022. [link]
[c.ml4]
Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi. Clustered
Sampling: Low–Variance and Improved Representativity for Clients Selection in
Federated Learning. Proceedings of the 38th International Conference on
Machine Learning, ICML,
3407-3416. PMLR, 2021. [link]
[c.ml5] Yann Fraboni,
Richard Vidal, Marco Lorenzi. Free–rider
Attacks on Model Aggregation in Federated Learning. AISTATS 2021 – 24th
International Conference on Artificial Intelligence and Statistics, p. 1846-1854. PMLR, 2021. [link]
[c.ml6]
Luigi Antelmi, Nicholas Ayache,
Philippe Robert and Marco Lorenzi. Sparse
Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous
Data. Proceedings of the 36th International Conference on Machine Learning,
ICML, 302-311. PMLR,
2019. [link]
[c.ml7]
Marco Lorenzi, Maurizio Filippone. Constraining
the Dynamics of Deep Probabilistic Models. Proceedings of the 35th
International Conference on Machine Learning, ICML, 3227-3236. PMLR, 2018. [link]
Highly selective medical imaging conferences (16) (acceptance rate ~25%)
[c.mi1] Riccardo Taiello, Melek Önen, Olivier Humbert, and Marco Lorenzi. Privacy Preserving Image Registration. In
Medical Image Computing and Computer-Assisted Intervention-MICCAI 2022. pp.
130-140. [link]
[c.mi2] Josquin Harrison, Marco Lorenzi, Benoit Legghe, Xavier Iriart, Hubert Cochet, and Maxime Sermesant.
Phase-independent latent representation for cardiac shape analysis. In
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021. Part VI
24, pp. 537-546. [link]
[c.mi3]
Irene Balelli, Santiago Silva, Marco Lorenzi. A probabilistic framework for modeling the variability across federated datasets. In
International Conference on Information Processing in Medical Imaging-IPMI 2021.
pp. 701-714. [link]
[c.mi4]
Jaume Banus, Maxime Sermesant, Oscar Camara, and Marco Lorenzi. Joint data imputation and mechanistic
modelling for simulating heart-brain interactions in incomplete datasets.
In Medical Image Computing and Computer Assisted Intervention, MICCAI 2020. Part
VI 23, pp. 478-486. [link]
[c.mi5]
Sara Garbarino, Marco Lorenzi. Modeling and inference of spatio-temporal
protein dynamics across brain networks. In Information Processing in
Medical Imaging-IPMI 2019. pp. 57-69. [link]
[c.mi6]
Georgios Lazaridis, Marco Lorenzi, Sebastien Ourselin, and
David Garway-Heath. Enhancing OCT signal by fusion
of GANs: improving statistical power of glaucoma clinical trials. In
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019. Part I
22, pp. 3-11. [link]
[c.mi7] Răzvan
Marinescu, Marco Lorenzi, Stefano B. Blumberg, Alexandra L. Young, Pere Planell-Morell, Neil P. Oxtoby, Arman Eshaghi
et al. Disease knowledge transfer across neurodegenerative diseases. In
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019. Part II
22, pp. 860-868. [link]
[c.mi8] Juan Eugenio
Iglesias, Marco Lorenzi, Sebastiano Ferraris, Loïc
Peter, Marc Modat, Allison Stevens, Bruce Fischl, and Tom Vercauteren. Model-based
refinement of nonlinear registrations in 3D histology reconstruction. In
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018. Part II
11, pp. 147-155. [link]
[c.mi9] Razvan Marinescu, Arman
Eshaghi, Marco Lorenzi,
Alexandra Young, Neil Oxtoby, Sara Garbarino, et al. A
vertex clustering model for disease progression: application to cortical
thickness images. In Information Processing in Medical Imaging-IPMI 2017. pp.
134-145. [link]
[c.mi10] Eliza Orasanu, Pierre-Louis Bazin,
Andrew Melbourne, Marco Lorenzi, Herve Lombaert, Nicola J. Robertson, Giles Kendall, Nikolaus
Weiskopf, Neil Marlow, and Sebastien Ourselin. Longitudinal
analysis of the preterm cortex using multi-modal spectral matching. In
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016. Part I
19, pp. 255-263. [link]
[c.mi11]
Marco Lorenzi, Gabriel Ziegler, Daniel Alexander, Sebastien Ourselin. Efficient Gaussian process-based modelling and
prediction of image time series. In Information Processing in Medical
Imaging-IPMI 2015. [link]
[c.mi12] Boris Gutman, Tom Fletcher,
Jorge Cardoso, Greg Fleishman, Marco Lorenzi, Paul
Thompson, Sebastien Ourselin. A Riemannian
framework for intrinsic comparison of closed genus-zero shapes. In
Information Processing in Medical Imaging-IPMI 2015. pp. 205-218. [link]
[c.mi13] Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, and
Xavier Pennec. A biophysical model of shape
changes due to atrophy in the brain with Alzheimer’s disease. In Medical
Image Computing and Computer-Assisted Intervention–MICCAI 2014. Part II 17, pp.
41-48. [link]
[c.mi14] Marco Lorenzi, Bjoern H. Menze, Marc Niethammer, Nicholas Ayache,
Xavier Pennec, and Alzheimer’s Disease Neuroimaging
Initiative. Sparse scale-space decomposition of volume changes in
deformations fields. In Medical Image Computing and Computer-Assisted
Intervention–MICCAI 2013. Part II 16, pp. 328-335. [link]
[c.mi15]
Marco Lorenzi, Nicholas Ayache, and
Xavier Pennec. Schild’s
ladder for the parallel transport of deformations in time series of images.
Biennial international conference on information processing in medical imaging
IPMI. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. [link]
[c.mi16] Marco Lorenzi,
Nicholas Ayache, and Xavier Pennec.
Regional flux analysis of longitudinal atrophy in Alzheimer’s disease.
In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012.
Part I 15, pp. 739-746. [link]
Machine learning workshops (2)
[w.ml1]
Etrit Haxholli and Marco Lorenzi. Enhanced Distribution Modelling via Augmented Architectures For Neural ODE Flows. In NeurIPS 2023 Workshop DLDE-III. [link]
[w.ml2]
Etrit Haxholli and Marco Lorenzi. Faster Training
of Diffusion Models and Improved Density Estimation via Parallel Score Matching.
In NeurIPS 2023 Workshop on Diffusion Models. [link]
Medical imaging conferences and workshops (17) (acceptance rate ~50%)
[w.mi1] Lucia Innocenti, Michela Antonelli, Francesco Cremonesi,
Kenaan Sarhan, Alejandro
Granados, Vicky Goh, Sébastien Ourselin, Marco Lorenzi. Benchmarking Collaborative
Learning Methods Cost-Effectiveness for Prostate Segmentation. PharML workshop at AAAI 2023. [link]
[w.mi2] Federica Cruciani, Andre Altmann, Marco Lorenzi, Gloria Menegaz, and
Ilaria Boscolo Galazzo. What
PLS can still do for Imaging Genetics in Alzheimer's disease. In 2022
IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI),
1-4. IEEE, 2022. [link]
[w.mi3] Marta Nunez Garcia, Sonny Finsterbach, Bunteng Ly, Marco Lorenzi, Hubert Cochet, and Maxime Sermesant.
Long-term remodelling and arrhythmogenicity after myocardial infarction
using a novel image-based estimator: the Scar Maturation Score. Europace 24, no. Supplement_1 (2022): euac053-042. [link]
[w.mi4]
Josquin Harrison, Marco Lorenzi, Benoit Legghe, Xavier Iriart, Hubert
Cochet, and Maxime Sermesant. Prediction of
thrombosis in atrial fibrillation with compact atrial shape representation.
Europace 24, no. Supplement_1 (2022): euac053-562. [link]
[w.mi5] Lorenza Brusini, Federica Cruciani,
Ilaria Boscolo Galazzo,
Marco Pitteri, Silvia F. Storti,
Massimiliano Calabrese, Marco Lorenzi, and Gloria Menegaz. Multivariate data analysis suggests the link
between brain microstructure and cognitive impairment in multiple sclerosis.
In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI),
685-688. IEEE, 2021. [link]
[w.mi6] Santiago Silva, Andre Altmann, Boris
Gutman, Marco Lorenzi. Fed–BioMed: A
general open–source frontend framework for federated learning in healthcare.
1st MICCAI Workshop on Distributed and Collaborative Learning, Oct 2020, Lima,
Peru. 201–210. [link]
[w.mi7] Marta Nuñez–Garcia, Nicolas Cedilnik, Shuman Jia, Hubert Cochet, Marco Lorenzi, and Maxime Sermessant. Estimation
of imaging biomarker's progression in post–infarct patients using
cross–sectional data. STACOM 2020 [link]
[w.mi8] Jaume Banus Cobo, Marco Lorenzi, Oscar Camara, Maxime
Sermesant. Large Scale Cardiovascular Model
Personalisation for Mechanistic Analysis of Heart and Brain Interactions.
Proceedings of the 10th International Conference on Functional Imaging and Modeling of the Heart (FIMH). [link]
[w.mi9] Santiago Silva, Boris Gutman, Barbara Bardoni, Paul M Thompson, Andre Altmann, Marco Lorenzi. Multivariate Learning in Distributed Biomedical
Databases: Meta-analysis of Large-scale Brain Imaging Data. IEEE
International Symposium on Biomedical Imaging (ISBI), Venice, 2019. [link]
[w.mi10] Marco Lorenzi, Boris Gutman, Paul M
Thompson, Daniel C Alexander, Sebastien Ourselin,
Andre Altmann. Secure multivariate large-scale multi-centric analysis
through on-line learning: an imaging genetics case study. 12th
International Symposium on Medical Information Processing and Analysis,
1016016, International Society for Optics and Photonics (SIPAIM), 2017. [link]
[w.mi11] Sebastiano
Ferraris, Marco Lorenzi, Pankaj Daga, Marc Modat, Tom Vercauteren. Accurate small deformation exponential
approximant to integrate large velocity fields: Application to image
registration. In Proceedings of the IEEE Conference on Computer Vision and
Pattern Recognition Workshops, 17-24, 2016. [link]
[w.mi12] Marco Lorenzi, Boris A. Gutman,
Derrek P. Hibar, Andre Altmann, Neda Jahanshad, Paul M. Thompson and Sebastien Ourselin. Partial Least Squares Modelling for Imaging
genetics in Alzheimer's Disease: Plausibility and Generalization. IEEE
International Symposium on Biomedical Imaging (ISBI), 2016. [link]
[w.mi13] Marco Lorenzi, Gabriel Ziegler,
Daniel C. Alexander, and Sebastien Ourselin. Modelling
Non-Stationary and Non-Separable Spatio-Temporal
Changes in Neurodegeneration via Gaussian Process Convolution, 1st ICML
Workshop on Machine Learning Meets Medical Imaging. 9487, Springer, LNCS, 2015.
[link]
[w.mi14] Marco Lorenzi and Xavier Pennec. Parallel Transport with Pole Ladder: Application
to Deformations of time Series of Images. In GSI2013 - Geometric Science of
Information, Springer, LNCS, 8085, 68-75, 2013. [link]
[w.mi15] Marco Lorenzi, Giovanni B. Frisoni, Nicholas Ayache, and
Xavier Pennec. Probabilistic Flux Analysis of
Cerebral Longitudinal Atrophy. In MICCAI workshop on Novel Imaging
Biomarkers for Alzheimer's Disease and Related Disorders (NIBAD 12), 256-265,
2012. [link]
[w.mi16] Marco Lorenzi and Xavier Pennec. Geodesics, parallel transport &
one-parameter subgroups. In 3rd MICCAI workshop on Mathematical Foundations
of Computational Anatomy Workshop, September 2011. [link]
[w.mi17] Marco Lorenzi, Nicholas Ayache, Giovanni B. Frisoni, and
Xavier Pennec. 4D registration of serial brain
MRIs images: a robust measure of changes applied to Alzheimer's disease. In
MICCAI Workshop on Spatio-Temporal Image Analysis for
Longitudinal and Time-Series Image Data, 2010. [link]
Books (1)
I am editor of the book Trustworthy AI in Medical
Imaging, which features 22 chapters from recognized authors from the
communities of medical imaging, machine learning and security. I was invited by
Elsevier to curate the book after I organised the homologous MICCAI workshop in 2022. The expected publication date is April 2024.
Book Chapters (4)
[b1]
Marco Lorenzi, Irene Balelli, Ana Aguila and Andre Altmann. Integration of
Multimodal Data. In Machine Learning for Brain Disorders. Editor: O. Colliot. Springer 2023. Chapter 19. [link]
[b2]
Marco Lorenzi and Andre Altmann. Imaging
Genetics. In Medical Image Analysis. Editors: A. Frangi,
J. Prince, and M. Sonka. Elsevier 2023. Chapter 21. [link]
[b3] Xavier Pennec, Marco Lorenzi. Beyond Riemannian
geometry: The affine connection setting for transformation groups. In Riemannian
Geometric Statistics in Medical Image Analysis. Editors: X. Pennec,
S. Sommer and T. Fletcher. Elsevier 2020. Chapter 5. [link]
[b4] Marco Lorenzi and Xavier Pennec. Discrete
Ladders for Parallel Transport in Transformation Groups with an Affine
Connection Structure. In Geometric Theory of Information Signals and
Communication Technology. Editor: Frank Nielsen. Springer 2014. pp. 243-271. [link]
Oral Presentations at Clinical Conferences (7)
[o.1] Marco
Lorenzi, Helene Barelli. Blood levels of Omega
3 and 6 across the progression of Alzheimer’s
disease. Alzheimer’s
Association International Conference (AAIC), 2019.
[o.2] Guoqiao Wang, Marco Lorenzi, Yan Li, Michael
C. Donohue, Eric Mcdade,
Andrew J. Aschenbrenner, Tammie L.S. Benzinger, Anne M. Fagan, Suzanne
E. Schindler, Jason Hassenstab, Scott Berry, John C.
Morris, Chengjie Xiong,
Randall Bateman. Estimating years from clinical
symptom onset for sporadic Alzheimer’s disease : how far are we? Alzheimer’s
Association International Conference (AAIC), 2019.
[o.3] Marco Lorenzi, Maurizio Filippone, Daniel C. Alexander, Sebastien
Ourselin. Modeling and prediction
of the natural history of Alzheimer’s disease from longitudinal trial data. Alzheimer’s
Association International Conference (AAIC), 2017.
[o.4] Marco Lorenzi, Boris A. Gutman, Andre Altmann, Derrek P. Hibar, Neda Jahanshad, Daniel C.
Alexander, Paul M. Thompson, Sebastien Ourselin. Linking Gene Pathways and Brain Atrophy in Alzheimer's Disease. Alzheimer’s Association International Conference
(AAIC), 2016.
[o.5] Marco Lorenzi, Nicholas Ayache,
Xavier Pennec. Regional
flux analysis of longitudinal atrophy
in Alzheimer’s disease.
Alzheimer’s Association International Conference (AAIC), 2014.
[o.6] Marco Lorenzi, Nicholas Ayache,
Xavier Pennec, Giovanni B. Frisoni.
Disentangling the normal aging from the pathological Alzheimer's disease progression on cross-sectional structural MR images.
International Conference on Clinical
Trials on Alzheimer's Disease
(CTAD), 2012.
[o.7] Marco Lorenzi, Michael Donohue, Donata Paternic, Cristina Scarpazza, Susan Ostrowitzki,
Olivier Blin, Elain Irving, Giovanni B. Frisoni. Enrichment through biomarkers in clinical trials of Alzheimer's drugs in patients with mild cognitive impairment.
International Conference on Clinical
Trials on Alzheimer's Disease
(CTAD), 2010.
Poster Presentations at Clinical Conferences (15)
[p.1] Jaume Banus, Marco
Lorenzi, Oscar Camara,
Maxime Sermesant. Large-scale
analysis of heart-brain
interactions through personalisation
of a mechanistic cardiovascular
model. Poster. Alzheimer’s Association
International Conference (AAIC), 2020.
[p.2] Damiano Archetti, Marco Lorenzi, Neil P. Oxtoby, Daniel C. Alexander, Giovanni
B. Frisoni, Alberto Redolfi.
Inter-cohort staging efficacy of gaussian process
progression model for Alzheimer’s disease.
Alzheimer’s Association International Conference (AAIC), 2020.
[p.3] Luigi Antelmi, Nicholas Ayache, Philippe Robert, Marco Lorenzi. Multiview analysis of clinical and MRI/PET imaging and socio-demographic data in Alzheimer’s
disease. Alzheimer’s
Association International Conference (AAIC), 2020.
[p.4] Clement Abi Nader, Nicholas Ayache, Philippe Robert, Marco Lorenzi. Simulating the outcome
of a clinical intervention from
a data-driven model of Alzheimer's
disease progression. Alzheimer’s
Association International Conference (AAIC), 2020.
[p.5] Radia Zeghari, Philippe Robert, Valeria Manera, Marco
Lorenzi, Alexandra König. Towards a multidimensional
assessment of apathy in
neurocognitive disorders. Alzheimer’s
Association International Conference (AAIC), 2020.
[p.6] Marzia
Antonella Scelsi, Marco Lorenzi, Jon M. Schott, Sebastien Ourselin, Andre Altmann. Genome-wide association study
of a multimodal imaging biomarker
in the ADNI cohort. Alzheimer’s
Association International Conference (AAIC), 2017.
[p.7] Neil P. Oxtoby, Alexandra L. Young, Marco Lorenzi, David M. Cash, Philip S.J. Weston, Sebastien Ourselin, Nick C. Fox,
Jon M. Schott, Daniel C. Alexander. Model-Based Comparison of Autosomal-Dominant and Late-Onset
Alzheimer's Disease
Progression in the Dian and ADNI Studies.
Alzheimer’s Association International Conference (AAIC), 2016.
[p.8] Razvan Valentin Marinescu, Alexandra L. Young, Neil
P. Oxtoby, Nicholas C. Firth, Marco Lorenzi, Arman Eshaghi, Viktor Wottschel, M. Jorge Cardoso, Marc Modat,
Keir Yong, Silvia Primativo,
Nick C. Fox, Manja Lehmann, Timothy J. Shakespeare,
Sebastian J. Crutch, Daniel C. Alexander. A
Data-Driven Comparison of the Progression of Brain Atrophy in Posterior Cortical Atrophy and Alzheimer's Disease. Alzheimer’s
Association International Conference (AAIC), 2016.
[p.9] Marco Lorenzi, Ivor Simpson, Alexander Mendelson,
Jorge M. Cardoso, Marc Modat, Sebastien
Ourselin. Voxel-based statistical multimodal model of brain
atrophy and hypometabolism
in Alzheimer's disease.
Alzheimer’s Association International Conference (AAIC), 2015.
[p.10] Marco Lorenzi, Martina Bocchetta, Nicholas Ayache, Xavier Pennec,
Giovanni Frisoni. Conversion to MCI in healthy individuals with abnormal CSF Aβ42 levels is associated
with specific longitudinal morphological changes of the brain.
Alzheimer’s Association International Conference (AAIC), 2013.
[p.11] Marco Lorenzi, Giovanni Frisoni, Nicholas Ayache, Xavier Pennec.
Spatio-temporal model of atrophy progression in healthy subjects at risk for Alzheimer's disease. Alzheimer’s Association International Conference
(AAIC), 2012.
[p.12] Marco Lorenzi, Giovanni Frisoni, Nicholas Ayache, Xavier Pennec.
Modeling the longitudinal atrophy in healthy subject at risk for Alzheimer's disease. Alzheimer’s
Association International Conference (AAIC), 2012.
[p.13] Moira Marizzoni, Edoardo
Micotti, Marco
Lorenzi, Alessandra Paladini, Anna Caroli, Claudia Balducci, Sophie Dix, Michael O'Neill, Christian Czech, Ozmen Laurence, Jill
Richardson, Gianluigi Forloni,
Giovanni Frisoni. In vivo diffusion tensor imaging and tract-based spatial statistics in three mouse models of Alzheimer's disease. Alzheimer’s Association International Conference
(AAIC), 2012.
[p.14] Marco Lorenzi, Xavier Pennec, Giovanni Frisoni. Monitoring
the Brain's Longitudinal Changes in Clinical Trials for Alzheimer's Disease:
A Robust and Reliable Nonrigid
Registration Framework. Alzheimer’s Association
International Conference (AAIC), 2011.
[p.15] Marco Lorenzi, Alberto Beltramello, Giada Zoccatelli, Francesca Benedetta Pizzini, Franco Alessandrini,
Maria Cotelli, Sandra Rosini, Elisa
Canu, Daniela Costardi,
Giovanni Frisoni. Effect
of memantine on the activity
of the default mode network : A resting fMRI study. Alzheimer’s Association International Conference
(AAIC), 2009.