Medial Mesh Research Articles

Medial hex-meshing: high-quality all-hexahedral mesh generation based on medial mesh

Medial hex-meshing: high-quality all-hexahedral mesh generation based on medial mesh

Robustly Extracting Concise 3D Curve Skeletons by Enhancing the Capture of Prominent Features.

Extracting concise 3D curve skeletons with existing methods is still a serious challenge as these methods require tedious parameter adjustment to suppress the influence of shape boundary perturbations to avoid spurious branches. In this paper, we address this challenge by enhancing the capture of prominent features and using them for skeleton extraction, motivated by the observation that the shape is mainly represented by prominent features. Our method takes the medial mesh of the shape as input, which can maintain the shape topology well. We develop a series of novel measures for simplifying and contracting the medial mesh to capture prominent features and represent them concisely, by which means the influences of shape boundary perturbations on skeleton extraction are suppressed and the quantity of data needed for skeleton extraction is significantly reduced. As a result, we can robustly and concisely extract the curve skeleton based on prominent features, avoiding the trouble of tuning parameters and saving computations, as shown by experimental results.

Point2MM: Learning medial mesh from point clouds

Medial mesh is the most commonly used representation of medial axis transform (MAT) which is a high-fidelity compact representation of 3D shape. Existing learning methods of extracting medial mesh from point clouds either have strict requirements of supervising training data, or are incapable of learning the complete form of medial mesh, leading to large reconstruction error. We introduce Point2MM, an unsupervised method for learning a complete medial mesh from point clouds. Our key idea is to use the envelop geometry of medial primitives – spheres, cones, and slabs – to capture the intrinsic geometry of shape, and the connectivity of medial mesh to capture the topology of shape. We firstly predict initial medial spheres by learning the geometric transformation of point clouds, then construct an initial connectivity of the medial spheres by learning the probability of medial cones and medial slabs with a novel unsupervised formulation. Finally we propose an iterative strategy for fine-tuning medial primitives. Extensive evaluations and comparisons show our method has superior accuracy and robustness in learning medial mesh from point clouds. In addition, the excessive training time is also a concern for our research, and it is a limitation where we need to make improvements in our future work.

P-085 MANAGEMENT OF LATERAL ABDOMINAL WALL HERNIAS

Abstract Lateral abdominal wall hernias are rare and inconsistently defined, which is why the use of the EHS classification makes sense, not least for the purpose of comparing the quality of surgical results. A distinction must be made between true fascial defects and denervation atrophy. Based on the available literature, there is generally a low level of evidence with no consensus on the best operative strategy. The proximity to bony structures and the complex anatomy of the three-layer abdominal wall make lateral hernias difficult to care for. The surgical variability include laparo-endoscopic, robotic, minimally- invasive, open or hybrid approaches with different mesh positions in relation to the layers of the abdominal wall. The extensive preperitoneal mesh reinforcement open, transperitoneally laparoscopic (TAPP) or endoscopic extraperitoneally (TEP, TES) has met with the greatest approval. The extent of the required medial mesh- overlap is determined by the distance between the medial defect boundary and the lateral edge of the straight rectus-abdominal muscles. The lateral pre- and retroperitoneal dissection can be extended into the homolateral retrorectus compartment by laterally incising the posterior rectus sheath or can even be expanded by crossing the midline behind the intact linea alba into the contralateral retrorectus compartment. The “intraperitoneal onlay meshplasty” (IPOM) is only a suitable procedure for smaller and closable defects, but it is also important as an “exit strategy” in the case of a defective peritoneum. All procedures are explained using clear illustrations which are protected by copyright and were exclusively published in German in “der Chirurg”.

Out‐of‐core Extraction of Curve Skeletons for Large Volumetric Models

AbstractExisting methods for skeleton extraction have limitations in terms of the amount of memory space available, as the model must be allocated to the random access memory. This challenges the treatment of out‐of‐core models. Although applying out‐of‐core simplification methods to the model can fit in memory, this would induce distortion of the model surface, and so causing the skeleton to be off‐centered or changing the topological structure. In this paper, we propose an efficient out‐of‐core method for extracting skeletons from large volumetric models. The method takes a volumetric model as input and first computes an out‐of‐core distance transform. With the distance transform, we generate a medial mesh to capture the prominent features for skeleton extraction, which significantly reduces the data size and facilitates the process of large models. At last, we contract the medial mesh in an out‐of‐core fashion to generate the skeleton. Experimental results show that our method can efficiently extract high‐quality curve skeletons from large volumetric models with small memory usage.

IMMAT: Mesh Reconstruction from Single View Images by Medial Axis Transform Prediction

The representation of a 3D shape is a key element for capturing the overall structure as well as the local details. In this paper, we propose to predict a mesh representation of the Medial Axis Transform (called medial mesh) as an intermediate representation with our IMMAT framework, to reconstruct the 3D shape from a single view image. Because the MAT contains the skeleton topology and local thickness information, it not only enhances the ability to reconstruct topologically complex shapes but also better preserves the local details with its thickness control. The framework consists of three modules. The Image2Sphere module predicts the medial spheres inside the shape surface and the Topology Prediction module predicts the topological relationship (skeleton) between the predicted spheres. Then the MAT Smoothing module smooths the predicted MAT and fine-tunes the coordinates and radii of the spheres by graph convolution. The final 3D surface can be reconstructed by converting the predicted MAT to an implicit surface through CSG operation and then extracting the boundary surface through Marching Cubes. Experimental results show that our method outperforms the state-of-the-art methods both quantitatively and qualitatively on the reconstruction task.

Management of lateral abdominal wall hernias

Lateral abdominal wall hernias are rare and inconsistently defined, which is why the use of the European Hernia Society classification makes sense, not least for the purpose of comparing the quality of surgical results. Adistinction must be made between true fascial defects and denervation atrophy. Based on the available literature, there is generally alow level of evidence with no consensus on the best operative strategy. The proximity to bony structures and the complex anatomy of the three-layer abdominal wall make the technical treatment of lateral hernias difficult. The surgical variations include laparoendoscopic, robotic, minimally invasive, open or hybrid approaches with different mesh positions in relation to the layers of the abdominal wall. The extensive preperitoneal mesh reinforcement open, transabdominal peritoneal (TAPP) laparoscopic repair or total extraperitoneal (TEP) endoscopic repair has met with the greatest approval. The extent of the required medial mesh overlap is determined by the distance between the medial defect boundary and the lateral edge of the straight rectus abdominus muscles. The medially directed preperitoneal and retroperitoneal dissection can be extended into the homolateral retrorectus compartment by laterally incising the posterior rectus sheath or by crossing the midline behind the intact linea alba into the contralateral retrorectus compartment. The intraperitoneal onlay mesh (IPOM) technique is asuitable procedure only for smaller defects with possible defect closure but it is also important as an exit strategy in the case of adefective peritoneum. Individualized prehabilitative and preconditioning measures are just as important as the assessment of preoperative anamnestic and clinical findings and risks with radiographic cross-sectional imaging diagnostics.

Medial IPC

We propose a framework of efficient nonlinear deformable simulation with both fast continuous collision detection and robust collision resolution. We name this new framework Medial IPC as it integrates the merits from medial elastics, for an efficient and versatile reduced simulation, as well as incremental potential contact, for a robust collision and contact resolution. We leverage medial axis transform to construct a kinematic subspace. Instead of resorting to projective dynamics, we use classic hyperelastics to embrace real-world nonlinear materials. A novel reduced continuous collision detection algorithm is presented based on the medial mesh. Thanks to unique geometric properties of medial axis and medial primitives, we derive closed-form formulations for identifying between-primitive collision within the reduced medial space. In the meantime, the implicit barrier energy that generates necessary repulsion forces for collision resolution is also formulated with the medial coordinate. In other words, Medial IPC exploits a universal reduced coordinate for simulation, continuous self-/collision detection, and IPC-based collision resolution. Continuous collision detection also allows more aggressive time stepping. In addition, we carefully implement our system with a heterogeneous CPU-GPU deployment such that massively parallelizable computations are carried out on the GPU while few sequential computations are on the CPU. Such implementation also frees us from generating training poses for selecting Cubature points and pre-computing their weights. We have tested our method on complicated deformable models and collision-rich simulation scenarios. Due to the reduced nature of our system, the computation is faster than fullspace IPC or other fullspace methods using continuous collision detection by at least one order. The simulation remains high-quality as the medial subspace captures intriguing and local deformations with sufficient realism.

Multi-fidelity Kriging-assisted structural optimization of whole engine models employing medial meshes

Finite element models of whole gas turbine engines, also known as whole engine models (WEMs), which consist of three-dimensional solid elements are not commonly used in design optimization studies due to the high computational cost of solving them for many designs. WEMs consisting of two-dimensional shell elements can be a suitable replacement for high-fidelity solid WEMs as they approximate the responses well while being significantly quicker to solve. However, in a surrogate-assisted optimization study, the accumulation of errors in the shell WEM evaluations can result in the construction of a surrogate model that can be somewhat misleading compared to the solid WEM response surface. Such a surrogate model could return promising designs that, when validated using solid WEMs, turn out to be suboptimal or infeasible. A novel approach which combines medial meshing and multi-fidelity surrogate modelling techniques is proposed to increase the feasibility of conducting whole engine optimization studies. We demonstrate the workflow for generating medial meshes on an engine intercasing geometry. The accuracy of medial mesh simulations with respect to solid mesh simulations is evaluated and discussed in the context of their suitability as a source of low-fidelity structural information for multi-fidelity surrogate models. The impact of this combination of techniques is subsequently illustrated using two case studies. The first case study is the optimization of an intermediate compressor casing for minimum mass with constraints on the casing stiffness. The results show that the multi-fidelity approach is able to find optimum designs that are equivalent to the expensive single-fidelity approach of using only solid mesh evaluations but at a significantly lower computational cost. The second case study is the optimization of a whole engine geometry. This case study serves to demonstrate the effectiveness of the multi-fidelity approach for solving realistic design problems.

Medial Meshes - A Compact and Accurate Representation of Medial Axis Transform.

The medial axis transform has long been known as an intrinsic shape representation supporting a variety of shape analysis and synthesis tasks. However, for a given shape, it is hard to obtain its faithful, concise and stable medial axis, which hinders the application of the medial axis. In this paper, we introduce the medial mesh, a new discrete representation of the medial axis. A medial mesh is a 2D simplicial complex coupled with a radius function that provides a piecewise linear approximation to the medial axis. We further present an effective algorithm for computing a concise and stable medial mesh for a given shape. Our algorithm is quantitatively driven by a shape approximation error metric, and progressively simplifies an initial medial mesh by iteratively contracting edges until the approximation error reaches a predefined threshold. We further demonstrate the superior efficiency and accuracy of our method over existing methods for medial axis simplification.

Operative findings in recurrent hernia after a Lichtenstein procedure

Background: Recurrence after inguinal herniorraphy continues to be a problem, although the Lichtenstein technique (anterior, open fixated sheet mesh) is associated with reduced recurrence rates. Recurrence after Lichtenstein repair is suspected to be caused by insufficient fixation and overlap at the pubic tubercle. Methods: A review was made of 87 records from operations for recurrence after a previous Lichtenstein procedure, based upon national and large area data bases, recording 95% (Denmark) and 50% (Sweden) of all inguinal hernia operations. Results: Direct recurrences were found in 62%, whereas the remaining recurrences were either indirect (17%), femoral (13%), or other/unclassified (8%). Conclusion: The most plausible explanation for the development of the direct recurrences is an insufficient medial mesh fixation and overlap over the pubic tubercle. Avoidance of more than half of the recurrences after the Lichtenstein repair may be obtained by increased attention to this specific technical aspect of the operation.