By Dr Sebastiano Barbieri

Conference Papers

Misha P. T. MPT; Barbieri S; Klaassen R; van Laarhoven HWM; Crezee H; While PT; Nederveen AJ; Gurney-Champion OJ, 2021, 'Improved unsupervised physics-informed deep learning for intravoxel-incoherent motion modeling', online, presented at ISMRM 2021, online, 15 May 2021 - 20 May 2021

Barbieri S; Thoeny H, 2017, 'Training an Artificial Neural Network by Diffusion-Weighted MRI Data to Differentiate Between Prostate Cancer With High and With Low Gleason Score', Honolulu, HI, USA, presented at ISMRM 25th Annual Meeting & Exhibition, Honolulu, HI, USA, 22 April 2017 - 27 April 2017

Barbieri S; Torresani B, 2013, 'Basis Selection for Increased Interclass Separability of EEG Signals', Pacific Grove, California, USA, presented at 5th International Brain-Computer Interface Meeting, Pacific Grove, California, USA

Barbieri S; Torresani B, 2013, 'Optimal time-frequency bases for EEG signal classification in BCI context', Brest, France, presented at GRETSI, Brest, France

Moltz JH; Braunewell S; Rühaak J; Heckel F; Barbieri S; Tautz L; Hahn HK; Peitgen HO, 2011, 'Analysis of variability in manual liver tumor delineation in CT scans', in Proceedings - International Symposium on Biomedical Imaging, pp. 1974 - 1977, http://dx.doi.org/10.1109/ISBI.2011.5872797

Barbieri S; Bauer M; Klein J; Nimsky C; Hahn H, 2011, 'Analyzing the Accuracy of Fiber Tracking in Infiltrated Regions via Tumor Growth Simulation', Providence, Rhode Island, USA, presented at IEEE Visualization, Working with Uncertainty Workshop, Providence, Rhode Island, USA

Barbieri S; Klein J; Nimsky C; Hahn HK, 2010, 'Assessing fiber tracking accuracy via diffusion tensor software models', in Progress in Biomedical Optics and Imaging - Proceedings of SPIE, http://dx.doi.org/10.1117/12.844215

Klein J; Grötsch A; Betz D; Barbieri S; Friman O; Stieltjes B; Hildebrandt H; Hahn HK, 2010, 'Qualitative and quantitative analysis of probabilistic and deterministic fiber tracking', in Progress in Biomedical Optics and Imaging - Proceedings of SPIE, http://dx.doi.org/10.1117/12.843472

Bauer MHA; Egger J; O'Donnell T; Barbieri S; Klein J; Freisleben B; Hahn HK; Nimsky C, 2010, 'A fast and robust graph-based approach for boundary estimation of fiber bundles relying on fractional anisotropy maps', in Proceedings - International Conference on Pattern Recognition, pp. 4016 - 4019, http://dx.doi.org/10.1109/ICPR.2010.1155

Barbieri S; Bauer M; Klein J; Nimsky C; Hahn H, 2010, 'A variational, nonparametric approach to the fuzzy segmentation of diffusion tensor images', Beijing, China, presented at MICCAI workshop on computational diffusion MRI (CDMRI), Beijing, China, 20 September 2010 - 24 September 2010

Bauer MHA; Barbieri S; Egger J; Kuhnt D; Klein J; Hahn HK; Freisleben B; Nimsky C, 2010, 'Segmentation of fiber tract systems with a beam-based approach and smoothing of the FA and angular cards', in CEUR Workshop Proceedings, pp. 147 - 151

Bauer M; Barbieri S; Klein J; Egger J; Kuhnt D; Hahn H; Freisleben B; Nimsky C, 2010, 'A Ray-based Approach for Boundary Estimation of Fiber Bundles Derived from Diffusion Tensor Imaging', Geneva, Switzerland, presented at Computer Assisted Radiology and Surgery, Geneva, Switzerland

Barbieri S; Klein J; Nimsky C; Hahn H, 2010, 'Towards Image-Dependent Safety Hulls for Fiber Tracking', Stockholm, Sweden, presented at ISMRM, Stockholm, Sweden

Barbieri S; Welk M; Weickert J, 2008, 'Variatlonal registration of tensor-valued images', in 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops, http://dx.doi.org/10.1109/CVPRW.2008.4562964

Conference Abstracts

Bharat C; Larney S; Barbieri S; Dobbins T; Jones NR; Hickman M; Gisev N; Ali R; Degenhardt L, 2021, 'The effect of prescriber, treatment, and client characteristics on retention in opioid agonist treatment: A 15-year retrospective cohort study', in PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, WILEY, Vol. 30, pp. 357 - 357, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000687807300726&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1

Welberry H; Jorm L; Schaffer A; Barbieri S; Hsu B; Harris M; Hall J; Brodaty H, 2021, 'Changing general practitioner when entering residential aged care: impact on psychotropic medicine use and polypharmacy in 2,250 Australians with dementia', in Australian Dementia Forum, presented at Australian Dementia Forum

Hungerford P; Barbieri S; Schuler T; Eade T, 2020, 'Data Standardisation in Radiotherapy Using Deep Learning', in SPIE Medical Imaging, Houston, Texas, presented at SPIE Medical Imaging, Houston, Texas

Welberry H; Brodaty H; Hsu B; Barbieri S; Jorm L, 2020, 'Impact of prior home care on length-of-stay in residential care for Australians living with dementia', in Australian Dementia Forum, Adelaide, Australia, presented at Australian Dementia Forum, Adelaide, Australia

Welberry H; Brodaty H; Hsu B; Barbieri S; Jorm L, 2020, 'Measuring dementia incidence within a cohort of 267,153 older Australians using routinely collected linked administrative data', in 34th International Conference of Alzheimer’s Disease, Singapore, presented at 34th International Conference of Alzheimer’s Disease, Singapore

Welberry H; Brodaty H; Hsu B; Barbieri S; Jorm L, 2020, 'Measuring dementia incidence within a cohort of 267,153 older Australians using routinely collected linked administrative data', in International Population Data Linkage Network, presented at International Population Data Linkage Network

Barbieri S; Perez Concha O; Kotwal S; Gallagher M; Ritchie A; Jorm L, 2019, 'A Deep Representation of Longitudinal EMR Data Used for Predicting Readmission to the ICU and Describing Patients-at-Risk', in HSRAANZ, Auckland, New Zealand, presented at HSRAANZ, Auckland, New Zealand

Welberry H; Brodaty H; Hsu B; Barbieri S; Jorm L, 2019, 'Impact of prior home care on length of stay in residential care for Australians with dementia', in HSRAANZ, Auckland, New Zealand, presented at HSRAANZ, Auckland, New Zealand

Welberry H; Brodaty H; Barbieri S; Hsu B; Jorm L, 2019, 'Transitions through aged care in the last five years of life among those with dementia', in Australian Dementia Forum, Hobart, TAS, Australia, presented at Australian Dementia Forum, Hobart, TAS, Australia

Welberry H; Brodaty H; Hsu B; Barbieri S; Jorm L, 2018, 'Estimating dementia incidence and prevalence with multiple linked datasets', in Australian Epidemiological Associating Meeting, Fremantle, WA, Australia, presented at Australian Epidemiological Associating Meeting, Fremantle, WA, Australia

Barbieri S; Steiger P; Kruse A; Ith M; Thoeny H, 2017, 'DW-MRI as an alternative to biopsy in renal allograft patients with deteriorating renal function: a preliminary study', in European Congress of Radiology, Vienna, Austria, presented at European Congress of Radiology, Vienna, Austria

Munz J; Boxler S; Barbieri S; Thoeny H, 2017, 'Multiparametric MRI (mpMRI) of the prostate based on PI-RADS version 2: detection rate and negative predictive value', in Swiss Congress of Radiology, Bern, Switzerland, presented at Swiss Congress of Radiology, Bern, Switzerland

Barbieri S; Brönnimann M; Boxler S; Thoeny H, 2016, 'Detecting High-Risk Prostate Cancer by Analysing the Histogram of ADC and IVIM Parameter Values', in Swiss Congress of Radiology, Davos, Switzerland, presented at Swiss Congress of Radiology, Davos, Switzerland

Barbieri S; Donati O; Froehlich J; Thoeny H, 2016, 'Impact of Vendor and Field Strength of the Magnetic Resonance Scanner on Measurements of IVIM Parameter Values in Abdominal Organs', in Swiss Congress of Radiology, Davos, Switzerland, presented at Swiss Congress of Radiology, Davos, Switzerland

Klein J; Weiler F; Barbieri S; Hirsch J; Geisler B; Hahn H, 2012, 'Novel Features of NeuroQLab - A Software Assistant for Evaluating Neuroimaging Data', in European Congress of Radiology, Vienna, Austria, presented at European Congress of Radiology, Vienna, Austria

Klein J; Weiler F; Barbieri S; Hirsch J; Geisler B; Hahn H, 2011, 'NeuroQLab - An Extendible Software Assistant for Efficient and Reproducible Evaluation of Neuroimaging Data', in European Congress of Radiology, Vienna, Austria, presented at European Congress of Radiology, Vienna, Austria

Bauer M; Egger J; Kuhnt D; Barbieri S; Klein J; Hahn H; Freisleben B; Nimsky C, 2010, 'Ein semi-automatischer graphbasierter Ansatz zur Bestimmungen des Randes von eloquenten Faserverbindungen des menschlichen Gehirns', in 44th DGBMT Annual Meeting, Rostock, Germany, presented at 44th DGBMT Annual Meeting, Rostock, Germany

Bauer M; Egger J; Kuhnt D; Barbieri S; Freisleben B; Nimsky C, 2010, 'Evaluation of Several Cost Functions for Min-Cut-Segmentation of Fiber Bundles in the Human Brain', in 61st Annual Meeting of the German Society of Neurosurgery (DGNC), Mannheim, Germany, presented at Neurowoche, Mannheim, Germany

Bauer M; Egger J; Barbieri S; Klein J; Kuhnt D; Hahn H; Freisleben B; Nimsky C, 2010, 'Ray-Based and Graph-Based Methods for Fiber Bundle Boundary Estimation', in Biosignal 2010, Berlin, Germany, presented at International Biosignal Processing Conference, Berlin, Germany

Preprints

Micheletti N; Marchesi R; Kuo NI-H; Barbieri S; Jurman G; Osmani V, 2023, Generative AI Mitigates Representation Bias and Improves Model Fairness Through Synthetic Health Data, http://dx.doi.org/10.1101/2023.09.26.23296163

Kuo NI-H; Perez-Concha O; Hanly M; Mnatzaganian E; Hao B; Di Sipio M; Yu G; Vanjara J; Valerie IC; de Oliveira Costa J; Churches T; Lujic S; Hegarty J; Jorm L; Barbieri S, 2023, Enriching Data Science and Health Care Education: Application and Impact of Synthetic Data Sets Through the Health Gym Project (Preprint), http://dx.doi.org/10.2196/preprints.51388

Kuo NI-H; Jorm L; Barbieri S, 2023, Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models, http://dx.doi.org/10.48550/arxiv.2303.12281

Kuo NI-H; Garcia F; Sönnerborg A; Zazzi M; Böhm M; Kaiser R; Polizzotto M; Jorm L; Barbieri S, 2022, Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIV, http://dx.doi.org/10.48550/arxiv.2208.08655

Kuo NI-H; Polizzotto MN; Finfer S; Garcia F; Sönnerborg A; Zazzi M; Böhm M; Jorm L; Barbieri S, 2022, The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithms, http://dx.doi.org/10.48550/arxiv.2203.06369

Kuo NI-H; Polizzotto M; Finfer S; Jorm L; Barbieri S, 2021, Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project, http://dx.doi.org/10.48550/arxiv.2112.03914

Liu J; Gallego B; Barbieri S, 2021, Incorporating Uncertainty in Learning to Defer Algorithms for Safe Computer-Aided Diagnosis, http://dx.doi.org/10.48550/arxiv.2108.07392

Barbieri S; Mehta S; Wu B; Bharat C; Poppe K; Jorm L; Jackson R, 2020, Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach, http://dx.doi.org/10.48550/arxiv.2011.14032

Kaandorp MPT; Barbieri S; Klaassen R; van Laarhoven HWM; Crezee H; While PT; Nederveen AJ; Gurney-Champion OJ, 2020, Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients, http://dx.doi.org/10.48550/arxiv.2011.01689

Barbieri S; Kemp J; Perez-Concha O; Kotwal S; Gallagher M; Ritchie A; Jorm L, 2019, Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk, http://dx.doi.org/10.48550/arxiv.1905.08547

Barbieri S; Gurney-Champion OJ; Klaassen R; Thoeny HC, 2019, Deep Learning How to Fit an Intravoxel Incoherent Motion Model to Diffusion-Weighted MRI, http://dx.doi.org/10.48550/arxiv.1903.00095

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