Defects to human crania are one kind of head bone damages, and cranial implants can be used to repair the defected crania. The automation of the implant design process is crucial in reducing the corresponding therapy time. Taking the cranial implant design problem as a special kind of shape completion task, an automatic cranial implant design workflow is proposed, which consists of a deep neural network for the direct shape prediction of the missing part of the defective cranium and conventional post-processing steps to refine the automatically generated implant. To evaluate the proposed workflow, we employ cross-validation and report an average Dice Similarity Score and boundary Dice Similarity Score of 0.81 and 0.81, respectively. We also measure the surface distance error using the 95th quantile of the Hausdorff Distance, which yields an average of 3.01 mm. Comparison with the manual cranial implant design procedure also revealed the convenience of the proposed workflow. In addition, a plugin is developed for 3D Slicer, which implements the proposed automatic cranial implant design workflow and can facilitate the end-users.

OBJECTIVES:The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models). However, a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instruments is missing. METHODS:We present MedShapeNet to translate data-driven vision algorithms to medical applications and to adapt state-of-the-art vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. We present use cases in classifying brain tumors, skull reconstructions, multi-class anatomy completion, education, and 3D printing. RESULTS:By now, MedShapeNet includes 23 datasets with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. CONCLUSIONS:MedShapeNet contains medical shapes from anatomy and surgical instruments and will continue to collect data for benchmarks and applications. The project page is: https://medshapenet.ikim.nrw/.

There are inevitable risks during zygomatic implant placement surgery, particularly due to the complex anatomical structure of the zygomatic maxillary and the limited operating space. In this study, we present a haptic based simulation system for trainees to rehearse the process of zygomatic implant placement surgery, providing them with a multi-dimensional perception of vision, touch, and hearing, so that they can effectively master relevant surgical skills. We realize a complete simulation of the zygomatic implantation process, including preoperative planning, model loading, real-time rendering, and two-stage implantation simulation. The implantation simulation is divided into two stages: free motion and implant placement. We use a surface contact model for haptic rendering during the free motion stage and a voxel model to achieve efficient removal of elements during the implant placement stage. The system also provides trainees with a user-friendly interface for importing personalized model data, customizing the implantation steps and selecting the appropriate surgical tool, which maximizes the reproduction of real surgical scenarios.

Introduction Researchers and engineers have found their importance in healthcare industry including recent updates in patient-specific implant (PSI) design. CAD/CAM technology plays an important role in the design and development of Artificial Intelligence (AI) based implants. The across the globe have their interest focused on the design and manufacturing of AI-based implants in everyday professional use can decrease the cost, improve patient's health and increase efficiency, and thus many implant designers and manufacturers practice. Areas covered The focus of this study has been to manufacture smart devices that can make contact with the world as normal people do, understand their language, and learn to improve from real-life examples. Machine learning can be guided using a heavy amount of data sets and algorithms that can improve its ability to learn to perform the task. In this review, artificial intelligence (AI), deep learning, and machine-learning techniques are studied in the design of biomedical implants. Expert opinion The main purpose of this article was to highlight important AI techniques to design PSIs. These are the automatic techniques to help designers to design patient-specific implants using AI algorithms such as deep learning, machine learning, and some other automatic methods.

In this article, we present a skull database containing 500 healthy skulls segmented from high-resolution head computed-tomography (CT) scans and 29 defective skulls segmented from craniotomy head CTs. Each healthy skull contains the complete anatomical structures of human skulls, including the cranial bones, facial bones and other subtle structures. For each craniotomy skull, a part of the cranial bone is missing, leaving a defect on the skull. The defects have various sizes, shapes and positions, depending on the specific pathological conditions of each patient. Along with each craniotomy skull, a cranial implant, which is designed manually by an expert and can fit with the defect, is provided. Considering the large volume of the healthy skull collection, the dataset can be used to study the geometry/shape variabilities of human skulls and create a robust statistical model of the shape of human skulls, which can be used for various tasks such as cranial implant design. The craniotomy collection can serve as an evaluation set for automatic cranial implant design algorithms.

Database of 500 High-resolution Healthy Human Skulls and 29 Craniotomy Skulls and Implants. If you use any part of the dataset, please use the following references for citation in your work: Li J., et al. MUG500+ Repository. Figshare, 2021. DOI: 10.6084/m9.figshare.9616319 Li J., et al. MUG500+: Database of 500 High-resolution Healthy Human Skulls and 29 Craniotomy Skulls and Implants. Data in Brief, Elsevier, 2021. A recorded tutorial video about the semi-automatic cranial implant design workflow with Geomagic Sculpt can be viewed at: https://www.youtube.com/watch?v=FzaR3ydjaSc

BACKGROUND:The patient-specific templates for osteotomy often have complex surface features. Using current commercial software to design such templates is quite complicated, tedious and unrepeatable.AIMS:In this study, a novel surgical planning system for oral and maxillofacial surgery named EasyTemplate is developed, aiming to help doctors shorten the modelling time and assure the reliability in template design.MATERIALS & METHODS:In the simplified design process of an osteotomy guide, the main template can be formed efficiently using a surface offsetting algorithm, which is based on isosurface extraction and oriented bounding box. Thereafter, the cutting grooves can be generated automatically.RESULTS:A complicated surgical guide could be built accurately in about 10 min. Clinical orthognathic cases were conducted successfully using osteotomy and repositioning templates designed by EasyTemplate.DISCUSSION:Compared with commercially available softwares, higher efficiency and simpler design process were achieved, moreover, the time cost is one-third or even less.CONCLUSION:EasyTemplate can be a useful alternative to traditional softwares. This software allows the auto-generation algorithm which helps avoid a tedious modeling process while providing basic shapes for designers.

Introduction: Various prefabricated maxillofacial implants are used in the clinical routine for the surgical treatment of patients. In addition to these prefabricated implants, customized CAD/CAM implants become increasingly important for a more precise replacement of damaged anatomical structures. This paper reviews the design and manufacturing of patient-specific implants for the maxillofacial area.Areas covered: The contribution of this publication is to give a state-of-the-art overview in the usage of customized facial implants. Moreover, it provides future perspectives, including 3D printing technologies, for the manufacturing of patient-individual facial implants that are based on patient’s data acquisitions, like Computed Tomography (CT) or Magnetic Resonance Imaging (MRI).Expert opinion: The main target of this review is to present various designing software and 3D manufacturing technologies that have been applied to fabricate facial implants. In doing so, different CAD designing software’s are discussed, which are based on various methods and have been implemented and evaluated by researchers. Finally, recent 3D printing technologies that have been applied to manufacture patient-individual implants will be introduced and discussed.

Surgical software is a computer program that helps surgeons to optimize surgical procedures before they enter the operation room. The surgical planning software lets surgeons manipulate a 3D computer model of the patients body. Through this, the exactness, dependability and safety of the surgery can be improved diverting the preoperative planning into real surgical guide. However, it is quite difficult to design and manufacture the surgical guide without proper clinical applications. This study lays the foundation of the importance of various clinical applications and 3D manufacturing technologies to help surgeons design and manufacture surgical templates with high accuracy and high efficiency to save more lives in lesser time.

Background/Objectives: Hyderabad comes as a major industrial city in Pakistan, which covers more than 1264 acres of land surrounded by industries. This big city is facing extreme air pollution problems. However, this study was carried out to evaluate the health problems caused by polluted air in Industrial SITE Area of Hyderabad. Methods/Statistical Analysis: Two different Questionnaires were carried out to conduct a survey, first one for basic health unit purpose at the clinic level and second for workers to observe any curious diseases relating to air pollution. Findings: Labors have 24% Cough, 18 % Dermatitis, 8% Exacerbation of asthma and 7% acute respiration inspection. In addition, huge negligence of following safety measures was also observed during the survey. Most of the workers were not using any personal protective equipment and were lacking awareness. Application/ Improvements: It is strongly recommended to follow safety rules and regulations at the workplace, enhance the trees plantation and air pollution equipment must be instated by industries. Keywords: Air Pollution, Diseases, Impact on Health and Hyderabad City, Industries

Microstructural deformation and fracture process is important for chip formation and finished surface quality during metal cutting. In this paper, discrete element method (DEM) is introduced to establish a heterogeneous material model for cutting simulation to understand the microstructural deformation and fracture behaviors. A typical heterogeneous engineering material, ISO 450-10 ductile iron, was selected for modeling and experiments. Graphite nodules and ferrite grains were modeled respectively for studying their deformation behaviors. Cutting force and chip morphology obtained by simulation were compared with the experimental results. It shows that lamellar structure and unequal segments form at the chip free surface, which was also observed by optical microscope (OM) and scanning electron microscopy (SEM). The deformed degree of graphite nodules is much higher than that of ferrite grains. In addition, cracks are prone to produce and the chip size becomes smaller as the cutting speed increases. The velocity field and stress distribution of material near the rake face were investigated and the relationship between stress and cutting speed was further discussed. The velocity fluctuation of discrete particles in heterogeneous model is more obvious due to the microstructures compared with that in homogeneous model. Furthermore, the stress of material changes significantly with the increase of cutting speed since velocity vortexes may occur, resulting in the occurrence of the fracture. The results demonstrate that the influences of microstructure on crack initiation and chip formation are more significant at high cutting speeds.

As cutting tool penetrates into workpiece, stress waves is induced and propagates in the workpiece. This paper aims to propose a two-dimensional discrete element method to analyze the stress waves effects during high speed milling. The dependence of the stress waves propagation characteristics on rake angle and cutting speed was studied. The simulation results show that the energy distribution of stress waves is more concentrated near the tool tip as the rake angle or the cutting speed increases. In addition, the density of initial cracks in the workpiece near the cutting tool increases when the cutting speed is higher. The high speed milling experiments indicate that the chip size decreases as the cutting speed increases, which is just qualitatively consistent with the simulation.