Advancing Wound Filling Extraction on 3D Faces:An Auto-Segmentation and Wound Face Regeneration Approach

Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications.In this paper,we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network.Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions.To achieve accurate segmentation,we conducted thorough experiments and selected a high-performing model from the trainedmodels.The selectedmodel demonstrates exceptional segmentation performance for complex 3D facial wounds.Furthermore,based on the segmentation model,we propose an improved approach for extracting 3D facial wound fillers and compare it to the results of the previous study.Our method achieved a remarkable accuracy of 0.9999993% on the test suite,surpassing the performance of the previous method.From this result,we use 3D printing technology to illustrate the shape of the wound filling.The outcomes of this study have significant implications for physicians involved in preoperative planning and intervention design.By automating facial wound segmentation and improving the accuracy ofwound-filling extraction,our approach can assist in carefully assessing and optimizing interventions,leading to enhanced patient outcomes.Additionally,it contributes to advancing facial reconstruction techniques by utilizing machine learning and 3D bioprinting for printing skin tissue implants.Our source code is available at https://github.com/SIMOGroup/WoundFilling3D.

Size effects in the uniaxial compressive properties of 3D printed models of rocks:an experimental investigation

Transparent physical models of real rocks fabricated using three-dimensional(3D)printing technology are used in photoelas-tic experiments to quantify the evolution of the internal stress and deformation fields of rocks.Therefore,they are rendered as an emerging powerful technique to quantitatively reveal the intrinsic mechanisms of rock failure.The mechanical behav-ior of natural rocks exhibits a significant size effect;however,limited research has been conducted on whether transparent physical models observe similar size effects.In this study,to make the transparent printed models accurately demonstrate the mechanical behavior of natural rocks and reveal the internal mechanism of the size effect in rock mechanical behavior,the size effect in 3D printed models of fractured and porous rocks under uniaxial compressive loading was investigated.Transparent cylindrical models with different sizes that contained different fractured and porous structures were printed using the fracture and porous characteristics extracted from natural coal and sandstone.The variation in uniaxial compres-sive strength and elastic modulus of fractured and porous models for increasing model sizes were obtained through uniaxial compression experiments.Finally,the influence of internal discontinuous structural features,such as fractures and pores,on the size effect pertaining to the mechanical behavior of the model was analyzed and elaborated by comparing it with the mechanical properties of the continuous homogeneous model without fractures and pores.The findings provided support and reference to analyze the size effect of rock mechanical behavior and the effect of the internal discontinuous structure using 3D printed transparent models.

Three-dimensional modeling in complex liver surgery and liver transplantation

Liver resection and transplantation are the most effective therapies for many hepatobiliary tumors and diseases.However,these surgical procedures are challenging due to the anatomic complexity and many anatomical variations of the vascular and biliary structures.Three-dimensional(3D)printing models can clearly locate and describe blood vessels,bile ducts and tumors,calculate both liver and residual liver volumes,and finally predict the functional status of the liver after resection surgery.The 3D printing models may be particularly helpful in the preoperative evaluation and surgical planning of especially complex liver resection and transplantation,allowing to possibly increase resectability rates and reduce postoperative complications.With the continuous developments of imaging techniques,such models are expected to become widely applied in clinical practice.

3D printing process selection model based on triangular intuitionistic fuzzy numbers in cloud manufacturing

The distributed and customized 3D printing can be realized by 3D printing services in a cloud manufacturing environment.As a growing number of 3D printers are becoming accessible on various 3D printing service platforms,there raises the concern over the validation of virtual product designs and their manufacturing procedures for novices as well as users with 3D printing experience before physical products are produced through the cloud platform.This paper presents a 3D model to help users validate their designs and requirements not only in the traditional digital 3D model properties like shape and size,but also in physical material properties and manufacturing properties when producing physical products like surface roughness,print accuracy and part cost.These properties are closely related to the process of 3D printing and materials.In order to establish the 3D model,the paper analyzes the model of the 3D printing process selection in the cloud platform.Triangular intuitionistic fuzzy numbers are applied to generate a set of 3D printers with the same process and material.Based on the 3D printing process selection model,users can establish the 3D model and validate their designs and requirements on physical material properties and manufacturing properties before printing physical products.

Cost-reduction strategies in massive genomics experiments

Many modern biology studies require deep, whole-genome sequencing of hundreds to thousands of samples. Although persamplecosts have dramatically decreased, the total budget for such massive genome sequencing constitutes a significantbarrier for poorly funded labs. The costly lab tools required for genomics experiments further hinder such studies. Here, weshare two strategies for extensively reducing the costs of massive genomics experiments, including miniaturization of theNEBNext Ultra II FS DNA Library Prep Kit for Illumina (reducing the per-sample total costs to ~ 1/6 of that charged byservice providers) and in-lab 3D model-designing of genomics tools. These strategies not only dramatically release fundingpressure for labs, but also provide students with additional training in hands-on genomics and 3D-model-designing skills,demonstrating the high potential for their application in genomics experiments and science education.