Monte Carlo-based in-depth morphological analysis of medullary cavity for designing personalized femoral stem.

Background: The design of femoral stem prostheses requires a precise understanding of the femoral marrow cavity. Traditional measurements of morphological parameters in the upper femur, particularly the medullary cavity and cortical region, are primarily based on coronal and sagittal axes, which may not fully capture the true three-dimensional structure of the femur.

Methods: Propose a Monte Carlo-based method for a more comprehensive analysis of the femoral marrow cavity, using CT scans of femurs from a selected group of patients.

Modeling of human muscle and its deformation.

There is a lack of volume preserving and reasonable deformation of human muscles during bones and joints movement in the field of digital orthopedics. A novel approach for modeling of human muscle and its deformation was put forward to effectively assist doctors in guiding patients to carry out rehabilitation exercises. Firstly, based on Magnetic Resonance Imaging (MRI) data, the generated slice images were used to extract the outer contour lines and then the corresponding contour lines and optimal matching points of the adjacent layer images were connected to construct the three-dimensional (3D) geometric models of the muscles; Secondly, the mapping relationship between parameters can be established through hierarchical definition of the muscle characteristics to realize the volume-preserving deformation of muscle; Finally, the movement of human joints can be realized based on the constraint range of joint movement, and the vector-valued dynamic fourth-order differential equation was proposed to make the characteristic curve dynamically simulate the process of muscle deformation, thereby forming the corresponding relationship between bone movement and muscle deformation.

Convenient design method for customized implants based on bionic vein structure features.

Matching implants to bones is crucial for customized orthopedic medicine. Existing methods for designing customized implants predominantly adopt the parameterized deformation method that uses a fragmented representation of semantic parameters. Such a representation cannot provide information integration management and therefore restricts the retrieval of information regarding implant features and the improvement of customized design efficiency.

FractureNet: A 3D Convolutional Neural Network Based on the Architecture of m-Ary Tree for Fracture Type Identification.

To address the problem of automatic identification of fine-grained fracture types, in this paper, we propose a novel framework using 3D convolutional neural network (CNN) to learn fracture features from voxelized bone models which are obtained by establishing isomorphic mapping from fractured bones to a voxelized template. The network, which is named FractureNet, consists of four discriminators forming a multi-stage hierarchy. Each discriminator includes multiple sub-classifiers.

Bone morphological feature extraction for customized bone plate design.

Fractures are difficult to treat because of individual differences in bone morphology and fracture types. Compared to serialized bone plates, the use of customized plates significantly improves the fracture healing process. However, designing custom plates often requires the extraction of skeletal morphology, which is a complex and time-consuming procedure.

Custom-designed orthopedic plates using semantic parameters and template.

To quickly construct and conveniently modify the ideal orthopedic plates for individuals, a novel approach for designing the customized orthopedic plates is put forward based on bone template and plate semantic parameters, thus avoiding the need for the detailed geometric operations and the design of orthopedic plates from scratch each time. Firstly, an average bone model (ABM) is created from the existing bone models, among which each bone has an equal contribution to the ABM, and then the template, which contains region of interest (ROI) and segmentation regions, is constructed based on the ABM. Secondly, attached on the template ROI, the abutted surface feature of an orthopedic plate is designed including definition of characteristic points and configuration of semantic parameters, with a directed graph proposed to define the constraint relationship between semantic parameters.

A Novel Computer-Aided Approach for Parametric Investigation of Custom Design of Fracture Fixation Plates.

The present study proposes an integrated computer-aided approach combining femur surface modeling, fracture evidence recover plate creation, and plate modification in order to conduct a parametric investigation of the design of custom plate for a specific patient. The study allows for improving the design efficiency of specific plates on the patients' femur parameters and the fracture information. Furthermore, the present approach will lead to exploration of plate modification and optimization.

Statistical Analyses of Femur Parameters for Designing Anatomical Plates.

Femur parameters are key prerequisites for scientifically designing anatomical plates. Meanwhile, individual differences in femurs present a challenge to design well-fitting anatomical plates. Therefore, to design anatomical plates more scientifically, analyses of femur parameters with statistical methods were performed in this study.

Design of Orthopedic Plates and Its Modification Based on Feature.

To quickly construct the orthopedic plates and to conveniently edit it, a novel method for designing the plates is put forward based on feature idea and parameterization. Firstly, attached to the existing or repaired bone model, the region of interest (ROI) is selected as the abutted surface of orthopedic plate, and the ROI is reconstructed to form a CAD surface. Secondly, the CAD surface is to be defined as a surface feature (SF) and then some semantic parameters are configured for it.