Author

S. Balabani

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 5

Signature Assays, Organisms & Methods

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Assay:imaging· 5 Approach:experimental assay· 3 Research Focus:benchmarking· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:dimensionality reduction· 1 Approach:microscopy & imaging analysis· 1

Frequent Co-Authors

M. Bonfanti· 4 shared G. Franzetti· 3 shared V. Diaz-Zuccarini· 3 shared C. Stokes· 2 shared V. Diaz· 2 shared C. Chatpattanasiri· 1 shared C. S. Lim· 1 shared C. Tanade· 1 shared

Activity by Year

2019-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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4 shared papersBioengineering

M. Bonfanti

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Author profile →

5 papers

Recent·Most cited

Aneurysmal Growth in Type-B Aortic Dissection: Assessing the Impact of Patient-Specific Inlet Conditions on Key Haemodynamic Indices

C. Stokes, D. Ahmed, N. Lind, F. Haupt, D. Becker, J. Hamilton, V. Muthurangu, H. von Tengg-Kobligk, G. Papadakis, s. balabani, V. Diaz

This study compares patient-specific inlet velocity profiles with uniform profiles in CFD simulations to assess their impact on hemodynamic indices in Type-B Aortic Dissection.

bioRxiv · Feb 12, 2023 · PreprintBioengineering

Towards Reduced Order Models via Robust Proper Orthogonal Decomposition to Capture Personalised Aortic Haemodynamics

C. Chatpattanasiri, G. Franzetti, M. Bonfanti, V. Diaz-Zuccarini, S. Balabani

This paper uses reduced order models and proper orthogonal decomposition to capture personalized aortic hemodynamics from in vitro data, showing that few modes can represent flow features accurately.

bioRxiv · Jan 21, 2023Bioengineering

A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics

C. Stokes, M. Bonfanti, Z. Li, J. Xiong, D. Chen, S. Balabani, V. Diaz

This paper introduces an MRI-based data fusion method for simulating aortic haemodynamics, achieving accurate and efficient patient-specific compliant simulations without CT data.

bioRxiv · May 15, 2021Bioengineering

Effective Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations with In Vivo and In Vitro Validation

G. Franzetti, M. Bonfanti, C. Tanade, C. S. Lim, J. Tsui, G. Hamilton, V. Diaz-Zuccarini, S. Balabani

This paper develops a computational framework to simulate AVM haemodynamics and predict embolisation outcomes, validated with clinical and experimental data.

bioRxiv · May 15, 2021Bioengineering

Patient-specific haemodynamic simulations of complex aortic dissections informed by commonly available clinical datasets

M. Bonfanti, G. Franzetti, G. Maritati, S. Homer-Vanniasinkam, S. Balabani, V. Diaz-Zuccarini

This study uses patient-specific CFD models with clinical data to analyze haemodynamics in Type-B aortic dissections, revealing insights into disease state and risk factors.

bioRxiv · Mar 30, 2019Bioengineering