bibtext: @InProceedings{ Nat_Pixel2Mechanics_MICCAI2024,
                   author = { Natarajan, Sai and Muñoz-Moya, Estefano and Ruiz Wills, Carlos and Piella, Gemma and Noailly, Jérôme and Humbert, Ludovic and González Ballester, Miguel A. },
                   title = { { Pixel2Mechanics: Automated biomechanical simulations of high-resolution intervertebral discs from anisotropic MRIs } },
                   booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024},
                   year = {2024},
                   publisher = {Springer Nature Switzerland},
                   volume = { LNCS 15007 },
                   month = {October},
                   pages = { pending },
                }
abstract: Intervertebral disc (IVD) degeneration poses demanding challenges for improved diagnosis and treatment personalization. Biomechanical simulations bridge the gap between phenotypes and functional mechanobiology. However, personalized IVD modelling is hindered by complex manual workflows to obtain meshes suitable for biomechanical analysis using clinical MR data. This study proposes Pixel2Mechanics: a novel pipeline for biomechanical finite element (FE) simulation of high-resolution IVD meshes out of low resolution clinical MRI. We use our geometrical deep learning framework incorporating cross-level feature fusion to generate meshes of the lumbar Annuli Fibrosis (AF) and Nuclei Pulposi (NP), from the L1-L2 to L4-L5 IVD. Further, we improve our framework by proposing a novel optimization method based on differentiable rendering. Next, a custom morphing algorithm based on the Bayesian Coherent Point Drift++ approach generates volumetric FE meshes from the surface meshes, preserving tissue topology through the whole cohort while capturing shape specificities. Daily load simulations on these FE model simulations were evaluated in three volumes within the IVD: the center of the NP and the two transition zones (posterior and anterior) on mechanical responses. These were compared with the results obtained with a manual segmentation procedure. This study delivers a fully automated pipeline performing patient-personalized simulations of L1-L2 to L4-L5 IVD spine levels from clinical MRIs. It facilitates functional modeling and further exploration of normal and pathological discs while minimizing manual intervention. These features position the pipeline as a promising candidate for future clinical integration. Our data & code will be made available at: http://www.pixel2mechanics.github.io
title: Pixel2Mechanics: Automated biomechanical simulations of high-resolution intervertebral discs from anisotropic MRIs
authors: Natarajan, Sai Muñoz-Moya, Estefano Ruiz Wills, Carlos Piella, Gemma Noailly, Jérôme Humbert, Ludovic González Ballester, Miguel A.