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AIRBI 2026: Recordings

16 Sep 2026

This page contains live recordings and hard copies (pdf files) of PowerPoint presentations at the Symposium on AI and Reconstruction for Biomedical Imaging held on 9-10 March 2026.

AIRBI Programme Sessions
Presenter Session Title Content
Guobao Wang Bridging Physics and Learning: a decade of kernel methods for image reconstruction, Watch video |
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Hyungjin Chung Test-time Adaptation in Diffusion Models for​Medical Image Reconstruction Watch video |
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Zekai Li Hybrid kernelised PET reconstructionallowing for negative values Watch video |
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George Webber

A Non-Overfitting Objective for​ PET Image Reconstruction

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Florian Knoll Exploring the limitations of deep learningfor MR image reconstruction Watch video |
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Julia Schnabel Self-supervised motion reconstruction for precision MR(A)I Watch video
Natascha Niessen INR meets Multi-Contrast MRI Reconstruction Watch video |
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Awards Ceremony Awards Ceremony Watch video |
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Daniel McGowan Clinical Implementation of New PET Reconstruction Methods Watch video |
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Yelmer Van Lune Self-supervised DL physics-guided reconstruction of quantitative MRI Watch video |
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Simon Cherry The Power & Challenges of Total-Body PET Dynamic Imaging Watch video |
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Erich Kobler DEALing with Image Reconstruction: Deep Attentive Least Squares Watch video
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Evangelos Papoutsellis Split, Skip, & Play for Tomographic Reconstruction Watch video
Alessandro Perelli Stochastic Multiresolution Image Sketching for Inverse Imaging Problems Watch video |
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Simon Arridge Inverse Problems in Radiative Transport Watch video
Joyita Dutta AI for Post-Reconstruction PET Image Enhancement Watch video |
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Zi Wang Physics-informed Synthetic Data Learning: Boosting Multi-Scenario Fast MRI Reconstruction Watch video |
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Yi Li Deep-Learned Beamforming for Coherent Multi-Transducer Ultrasound Systems Watch video |
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Jinyi Qi Image Reconstruction for Positronium Lifetime Tomography Watch video |
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Zakhar Shumaylov Image Reconstruction in the Era of AI Watch video
Corentin Constanza Jacobian-Free Unrolling: memory-efficient unrolled network for 3D SPECT recon Watch video |
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Movindu Dassanayake List-Mode Data Derived Synthetic PET Image Reconstruction Watch video |
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Alexandre Bousse Closing remarks Watch video
Daniel Sanderson Variational Diffusion Reconstruction for Multiple CT Artifact Correction Watch video |
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Sam Porter Accelerating Joint PET/SPECT/CT Reconstruction with Preconditioning & Variance Reduction Watch video |
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Jae Sung Lee The Evolving Roles of AI in Nuclear Medicine Watch video |
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Georg Schramm AI in Medicine: Recommendations of the German Radiation Protection Commission Watch video
Abolfazl Mehranian Al Advances in Quantitative Molecular Imaging in industry Watch video |
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Julián Tachella Equivariant splitting: self-supervised learning from incomplete data Watch video |
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Andrew Wang Get started with Deeplnverse for image reconstruction with deep learning Watch video |
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Kris Thielemans Closing remarks Watch video |
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