[
    {
        "id": "osp-15923",
        "type": "article-journal",
        "title": "Local2Mesh: Spatially Localized Contour-to-Mesh for Left Ventricular Reconstruction from Sparse 2D Cardiac MRI",
        "author": [
            {
                "family": "Wu",
                "given": "Haoyu"
            },
            {
                "family": "Lin",
                "given": "Ling"
            },
            {
                "family": "Lefèvre",
                "given": "Pascal"
            },
            {
                "family": "Li",
                "given": "Ruizhe"
            },
            {
                "family": "Sun",
                "given": "Xiaowu"
            }
        ],
        "URL": "https://omanscience.com/en/articles/local2mesh-spatially-localized-contour-to-mesh-for-left-ventricular-reconstruction-from-sparse-2d-cardiac-mri",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "Three-dimensional (3D) left ventricular (LV) reconstruction from sparse cardiac magnetic resonance (CMR) imaging remains challenging due to inter-slice misalignment and insufficient local spatial information between slices. Global aggregation of contour features may obscure local contour-to-surface relationships. We propose Local2Mesh, a spatially localized contour-to-mesh framework that deforms a template mesh to reconstruct 3D LV geometry from sparse 2D contours without 3D mesh annotations. The framework introduces geometry-aware alignment to correct inter-slice misalignment and a plane-aware Local Router that routes contour features to template vertices using vertex-to-plane distances. Local and global contour features then jointly guide graph-based template deformation for 3D LV reconstruction. Experiments on two public datasets, M\\&Ms-2 and ACDC, demonstrate superior geometric reconstruction and functional estimation over existing methods. Zero-shot transfer from M\\&Ms-2 to ACDC demonstrates strong cross-dataset generalization. Reconstructed meshes also improve disease classification over sparse contours, supporting their utility for downstream cardiac analysis. These results demonstrate that combining geometry-aware alignment with local contour-to-vertex modeling improves LV reconstruction from sparse 2D contours and supports downstream cardiac analysis. The code is available at https://github.com/hwu918945-alt/loca2mesh."
    }
]