3D Feature Line Detection Based on Vertex Labeling and 2D Skeletonization

Kudelski, Dimitri; Mari, Jean-Luc; Viseur, Sophie

doi:10.1109/smi.2010.35

Cited by 10 publications

(6 citation statements)

References 18 publications

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“…Some of these conditions are shown in Fig. 1 C. New methods have improved the quality and repeatability of predicted network topology and connectivity; both deep learning models and traditional computer vision techniques have made significant advances in 2D/ 3D biological segmentations (59)(60)(61)(62). Despite these advances, current skeletonization methods continue to require semimanual postprocessing because of the ambiguities present in the structures during imaging and errors resulting from the image capturing modalities.…”

Section: Dlite Is Robust To Digitization Ambiguitiesmentioning

confidence: 99%

DLITE Uses Cell-Cell Interface Movement to Better Infer Cell-Cell Tensions

Vasan

Maleckar

Williams

et al. 2019

Biophysical Journal

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Cell shapes and connectivities evolve over time as the colony changes shape or embryos develop. Shapes of intercellular interfaces are closely coupled with the forces resulting from actomyosin interactions, membrane tension, or cell-cell adhesions. Although it is possible to computationally infer cell-cell forces from a mechanical model of collective cell behavior, doing so for temporally evolving forces in a manner robust to digitization difficulties is challenging. Here, we introduce a method for dynamic local intercellular tension estimation (DLITE) that infers such evolution in temporal force with less sensitivity to digitization ambiguities or errors. This method builds upon previous work on single time points (cellular force-inference toolkit). We validate our method using synthetic geometries. DLITE’s inferred cell colony tension evolutions correlate better with ground truth for these synthetic geometries as compared to tension values inferred from methods that consider each time point in isolation. We introduce cell connectivity errors, angle estimate errors, connection mislocalization, and connection topological changes to synthetic data and show that DLITE has reduced sensitivity to these conditions. Finally, we apply DLITE to time series of human-induced pluripotent stem cell colonies with endogenously expressed GFP-tagged zonulae occludentes-1. We show that DLITE offers improved stability in the inference of cell-cell tensions and supports a correlation between the dynamics of cell-cell forces and colony rearrangement.

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Section: Dlite Is Robust To Digitization Ambiguitiesmentioning

confidence: 99%

DLITE Uses Cell-Cell Interface Movement to Better Infer Cell-Cell Tensions

Vasan

Maleckar

Williams

et al. 2019

Biophysical Journal

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“…The connectivity ensures that all the points, or vertices, of a graph are linked together. In Kudelski et al (2010), the connectivity is assured using a vertex labeling step and mathematical morphological operators to extract feature lines. As these operators respect the topology of the objects, the connectivity of the resulting feature lines is guaranteed.…”

Section: Sulcal Features Extractionmentioning

confidence: 99%

“…First, we applied a noise-reduction algorithm on the curvature maps. Then, each vertex was labeled in order to define regions of interest (Kudelski et al 2010). Finally, the sulcal lines were extracted from these regions using topological operators to ensure the connectivity of the extracted lines.…”

Section: Sulcal Features Extractionmentioning

confidence: 99%

Quantitative in vivo MRI measurement of cortical development in the fetus

et al. 2011

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Normal brain development is associated with expansion and folding of the cerebral cortex following a highly orchestrated sequence of gyral-sulcal formation. Although several studies have described the evolution of cerebral cortical development ex vivo or ex utero, to date, very few studies have characterized and quantified the gyrification process for the in vivo fetal brain. Recent advances in fetal magnetic resonance imaging and post-processing computational methods are providing new insights into fetal brain maturation in vivo. In this study, we investigate the in vivo fetal cortical folding pattern in healthy fetuses between 25 and 35 weeks gestational age using 3-D reconstructed fetal cortical surfaces. We describe the in vivo fetal gyrification process using a robust feature extraction algorithm applied directly on the cortical surface, providing an explicit delineation of the sulcal pattern during fetal brain development. We also delineate cortical surface measures, including surface area and gyrification index. Our data support an exuberant third trimester gyrification process and suggest a non-linear evolution of sulcal development. The availability of normative indices of cerebral cortical developing in the living fetus may provide critical insights on the timing and progression of impaired cerebral development in the high-risk fetus.

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“…In order to define sets over triangulated 3D meshes, we use the algorithm proposed by Kudelski et al [14]. We compute the mean curvature H through a local polynomial fitting in the least-squares sense [12].…”

Section: 4mentioning

confidence: 99%