A Computational Tool for Pre-operative Breast Augmentation Planning in Aesthetic Plastic Surgery

Abstract—Breast augmentation was the most commonly performed cosmetic surgery procedure in 2011 in the United States. Although aesthetically pleasing surgical results can only be achieved if the correct breast implant is selected from a large variety of different prosthesis sizes and shapes available on the market, surgeons still rely on visual assessment and other subjective approaches for operative planning because of lacking objective evaluation tools. In this paper we present the development of a software prototype for augmentation mammaplasty simulation solely based on 3D surface scans, from which patient-specific finite element models are generated in a semi-automatic process. The finite element model is used to pre-operatively simulate the expected breast shapes using physical soft tissue mechanics. Our approach uses a novel mechanism based on so-called displacement templates, which, for a specific implant shape and position, describe the respective internal body forces. Due to a highly efficient numerical solver we can provide immediate visual feedback of the simulation results, and thus the software prototype can be integrated smoothly into the medical workflow. The clinical value of the developed 3D computational tool for aesthetic breast augmentation surgery planning is demonstrated in patientspecific use cases

Tissue Engineering in Oral and Maxillofacial Surgery : From Lab to Clinics

Regenerative medicine aims at the functional restoration of tissue malfunction, damage or loss, and can be divided into three main approaches. Firstly, the cell-based therapies, where cells are administered to re-establish a tissue either directly or through paracrine functions. Secondly, the often referred to as classical tissue engineering, consisting of the combined use of cells and a bio-degradable scaffold to form tissue. Thirdly, there are material-based approaches, which have made significant advances which rely on biodegradable materials, often functionalized with cellular functions (De Jong et al. 2014). In 1993, Langer and Vacanti, determined tissue engineering as an “interdisciplinary field that applies the principles of engineering and the life sciences toward the development of biological substitutes that restore, maintain, or improve tissue function”. They published this definition in Science in 1993. Tissue engineering has been classically thought to consist of three elements: supporting scaffold, cells and regulating factors such as growth factors (Fig. 1). Depending on the tissue to be regenerated, all three vary. Currently, it is known, that many other factors may have an effect on the outcome of the regenerate. These include factors enabling angiogenesis, physical stimulation, culture media, gene delivery and methods to deliver patient specific implants (PSI) (Fig. 2). During the past two decades, major obstacles have been tackled and tissue engineering is currently being used clinically in some applications while in others it is just taking its first baby steps.Peer reviewe

A numerical study on the influence of curvature ratio and vegetation density on a partially vegetated U-bend channel flow

Aquatic vegetation dramatically shifts the main flow, secondary flow and turbulent structures in a meandering channel. In this study, hydrodynamics in a bending channel with a vegetation patch (VP) has been numerically studied under the variation of curvature ratios (CRs=0.5, 1.0, 1.5, 2.0) and the vegetation density i.e. Solid Volume Fractions (SVF=1.13%, 4.86%). Both effects on vegetation shear flow, helical flow, bed shear stress and bulk drag coefficients are studied in twelve cases by using Ansys Fluent package. Unsteady Reynolds Averaging Navier-Stokes (URANS) framework coupled with the Reynolds Stress turbulence Model (RSM) and Volume Of Fluid (VOF) approach is successfully applied to predict the entire flow field including multi-circulation cells as well as the free surface. The conclusions are summarized as three points. Firstly, an increase of CR moves the main circulation cell and thalweg's location towards the outer bank, while decreasing the drag coefficients in streamwise and spanwise. However, the CR weakly affects the normalised shear flow velocity profiles and dominant eddy frequencies downstream of the VP. Secondly, the trend of the dominant shedding frequency to fall with the increase of SVF that has been known only for SVF<3.4% is extended up to 10.4%. Furthermore, an opposite trend is found between the frequency and SVF for 10.4%<SVF<20%. Thirdly, a newly proposed patch dimensionless frequency number, , links Stp and SVF, where N is the number of stems in the patch. This number stays almost constant for each case series regardless of the variation of SVF (for SVF<10.4%). We also conclude that is strongly determined by the patch shape factor, mildly influenced by the patch Reynolds number, but it excludes the influence of the SVF and N. The insights from the present study unveil the complicated eco-hydro-morphic interactions among the bio-mass density, turbulent flow and channel meanders’ variation. It provides a better understanding of natural bending river systems’ development and fundamentals for the recovery of urban channel ecosystems by vegetated re-meandering

A Process for the Semi-Automated Generation of Life-Sized, Interactive 3D Character Models for Holographic Projection

By mixing digital data into the real world, Augmented Reality (AR) can deliver potent immersive and interactive experience to its users. In many application contexts, this requires the capability to deploy animated, high fidelity 3D character models. In this paper, we propose a novel approach to efficiently transform – using 3D scanning – an actor to a photorealistic, animated character. This generated 3D assistant must be able to move to perform recorded motion capture data, and it must be able to generate dialogue with lip sync to naturally interact with the users. The approach we propose for creating these virtual AR assistants utilizes photogrammetric scanning, motion capture, and free viewpoint video for their integration in Unity. We deploy the Occipital Structure sensor to acquire static high-resolution textured surfaces, and a Vicon motion capture system to track series of movements. The proposed capturing process consists of the steps scanning, reconstruction with Wrap 3 and Maya, editing texture maps to reduce artefacts with Photoshop, and rigging with Maya and Motion Builder to render the models fit for animation and lip-sync using LipSyncPro. We test the approach in Unity by scanning two human models with 23 captured animations each. Our findings indicate that the major factors affecting the result quality are environment setup, lighting, and processing constraints

Quantifying Human Impacts on River Bar Morphology Using Digital Photogrammetry

Historically, the study of fluvial geomorphology has been dominated by the field method of surveying using a level and surveying rod. Beginning in the 1980s, the use of ground based and aerial LiDAR increased in popularity as a surveying method. However, LIDAR is expensive and requires significant training to operate. In recent years there has been an increase in the applicability of digital photogrammetry in the field of fluvial geomorphology. Lower costs, streamlined training and an increased accuracy all make digital photogrammetry a promising tool for the field geomorphologist. A study of the morphologic changes of four river bars on the Browns Canyon section of the Arkansas River, Colorado is used to explore the potential of digital photogrammetry by attempting to quantify the impacts of recreation river users on bar morphology. By creating high resolution digital elevation models (DEMs) at time intervals from 24 hours to several days, DEMs of difference (DoDs) were created and analyzed using the open-source 3D data processing software CloudCompare. DoDs were correlated with historical, daily commercial river user data to derive a relationship. Verification concerning the validity of CloudCompare was done using a simple experiment simulating erosion and deposition of a known volume of material

Aerodynamic Response of a Pitching Airfoil with Pulsed Circulation Control for Vertical Axis Wind Turbine Applications

Vertical Axis Wind Turbines (VAWTs) have experienced a renewed interest in development for urban, remote, and offshore applications. Past research has shown that VAWTs cannot compete with Horizontals Axis Wind Turbines (HAWTs) in terms of energy capture efficiency. VAWT performance is plagued by dynamic stall (DS) effects at low tip-speed ratios (lambda), where each blade pitches beyond static stall multiple times per revolution. Furthermore, for lambda\u3c2, blades operate outside of stall during over 70% of rotation. However, VAWTs offer many advantages such as omnidirectional operation, ground proximity of generator, lower sound emission, and non-cantilevered blades with longer life. Thus, mitigating dynamic stall and improving VAWT blade aerodynamics for competitive power efficiency has been a popular research topic in recent years and the directive of this study.;Past research at WVU focused on the addition of circulation control (CC) technology to improve VAWT aerodynamics and expand the operational envelope. A novel blade design was generated from the augmentation of a NACA0018 airfoil to include CC capabilities. Static wind tunnel data was collected for a range of steady jet momentum coefficients (0.01≤ Cmu≤0.10) for analytical vortex model performance projections. Control strategies were developed to optimize CC jet conditions throughout rotation, resulting in improved power output for 2≤lambda≤5. However, the pumping power required to produce steady CC jets reduced net power gains of the augmented turbine by approximately 15%. The goal of this work was to investigate pulsed CC jet actuation to match steady jet performance with reduced mass flow requirements. To date, no experimental studies have been completed to analyze pulsed CC performance on a pitching airfoil.;The research described herein details the first study on the impact of steady and pulsed jet CC on pitching VAWT blade aerodynamics. Both numerical and experimental studies were implemented, varying Re, k, and +/-alpha to match a typical VAWT operating environment. A range of reduced jet frequencies (0.25≤St≤4) were analyzed with varying Cmu, based on effective ranges from prior flow control airfoil studies. Airfoil pitch was found to increase the baseline lift-to-drag ratio (L/D) by up to 50% due to dynamic stall effects. The influence of dynamic stall on steady CC airfoil performance was greater for Cmu=0.05, increasing L/D by 115% for positive angle-of-attack. Pulsed actuation was shown to match, or improve, steady jet lift performance while reducing required mass flow by up to 35%. From numerical flow visualization, pulsed actuation was shown to reduce the size and strength of wake vorticity during DS, resulting in lower profile drag relative to baseline and steady actuation cases. A database of pitching airfoil test data, including overshoot and hysteresis of aerodynamic coefficients (Cl, Cd), was compiled for improved analytical model inputs to update CCVAWT performance predictions, where the aforementioned L/D improvements will be directly reflected.;Relative to a conventional VAWT with annual power output of 1 MW, previous work at WVU proved that the addition of steady jet CC could improve total output to 1.25 MW. However, the pumping cost to generate the continuous jet reduced yearly CCVAWT net gains to 1.15 MW. The current study has shown that pulsed CC jets can recover 4% of the pumping demands due to reduced mass flow requirements, increasing annual CCVAWT net power production to 1.19 MW, a 19% improvement relative to the conventional turbine

Intelligent Sensors for Human Motion Analysis

The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems

Information embedding and retrieval in 3D printed objects

Deep learning and convolutional neural networks have become the main tools of computer vision. These techniques are good at using supervised learning to learn complex representations from data. In particular, under limited settings, the image recognition model now performs better than the human baseline. However, computer vision science aims to build machines that can see. It requires the model to be able to extract more valuable information from images and videos than recognition. Generally, it is much more challenging to apply these deep learning models from recognition to other problems in computer vision. This thesis presents end-to-end deep learning architectures for a new computer vision field: watermark retrieval from 3D printed objects. As it is a new area, there is no state-of-the-art on many challenging benchmarks. Hence, we first define the problems and introduce the traditional approach, Local Binary Pattern method, to set our baseline for further study. Our neural networks seem useful but straightfor- ward, which outperform traditional approaches. What is more, these networks have good generalization. However, because our research field is new, the problems we face are not only various unpredictable parameters but also limited and low-quality training data. To address this, we make two observations: (i) we do not need to learn everything from scratch, we know a lot about the image segmentation area, and (ii) we cannot know everything from data, our models should be aware what key features they should learn. This thesis explores these ideas and even explore more. We show how to use end-to-end deep learning models to learn to retrieve watermark bumps and tackle covariates from a few training images data. Secondly, we introduce ideas from synthetic image data and domain randomization to augment training data and understand various covariates that may affect retrieve real-world 3D watermark bumps. We also show how the illumination in synthetic images data to effect and even improve retrieval accuracy for real-world recognization applications

Scan4Façade: Automated As-Is Façade Modeling of Historic High-Rise Buildings Using Drones and AI

This paper presents an automated as-is façade modeling method for existing and historic high-rise buildings, named Scan4Façade. To begin with, a camera drone with a spiral path is employed to capture building exterior images, and photogrammetry is used to conduct three-dimensional (3D) reconstruction and create mesh models for the scanned building façades. High-resolution façade orthoimages are then generated from mesh models and pixelwise segmented by an artificial intelligence (AI) model named U-net. A combined data augmentation strategy, including random flipping, rotation, resizing, perspective transformation, and color adjustment, is proposed for model training with a limited number of labels. As a result, the U-net achieves an average pixel accuracy of 0.9696 and a mean intersection over union of 0.9063 in testing. Then, the developed twoStagesClustering algorithm, with a two-round shape clustering and a two-round coordinates clustering, is used to precisely extract façade elements’ dimensions and coordinates from façade orthoimages and pixelwise label. In testing with the Michigan Central Station (office tower), a historic high-rise building, the developed algorithm achieves an accuracy of 99.77% in window extraction. In addition, the extracted façade geometric information and element types are transformed into AutoCAD command and script files to create CAD drawings without manual interaction. Experimental results also show that the proposed Scan4Façade method can provide clear and accurate information to assist BIM feature creation in Revit. Future research recommendations are also stated in this paper