From CT Scan to Plantar Pressure Map Distribution of a 3D Anatomic Human Foot

Total Page:16

File Type:pdf, Size:1020Kb

From CT Scan to Plantar Pressure Map Distribution of a 3D Anatomic Human Foot Excerpt from the Proceedings of the COMSOL Conference 2010 Paris From CT Scan to Plantar Pressure Map Distribution of a 3D Anatomic Human Foot P. Franciosa, S. Gerbino* University of Molise, School of Engineering *Corresponding author: Via Duca degli Abruzzi - 86039 Termoli (CB) – Italy [email protected] Abstract: Understanding the stress-strain behav- methods, based on FE modeling, have also been ior of human foot tissues and pressure map dis- adopted. FE models of human foot have been tributions at the plantar interface is of interest developed under certain simplifications and as- into biomechanical investigations. In particular, sumptions (see [7] and [8]) such as: (i) simplified monitoring plantar pressure maps is crucial to or partial foot shape, (ii) assumptions of non- establishing the perceived human comfort of linear hyper-elastic material law, (iii) ligaments shoe insoles. and plantar fascia modeled as equivalent forces In this contest, a 3D anatomical detailed FE hu- or elastic beams/bars, (iiii) no friction or thermal man foot model was created, starting from CT effect, at plantar foot interface, accounted. (Computer Tomography) scans of a 29 years old Based on these assumptions, valuable 3D FE male. Anatomical domains related to bones and models were presented in the literature [9], [10]. soft tissues were generated, using segmentation In this contest, the geometrical complexity of techniques, and then processed into a CAD envi- foot structure was captured through reverse en- ronment to model 3D domains by using gineering methodologies, based on CT (Com- loft/sweep and boolean operations. Finally, FE puter Tomography) or MR (Magnetic Reso- model was generated into Comsol Multiphys- nance) scans. Starting from high resolution ics® 3.5a, by assigning contact pairs and defin- medical images, suitable FE models were gener- ing non-linear material laws. Particular attention ated by using segmentation procedures. was posed on fine tuning the calculation strongly In the present paper, how to face out the 3D dependent on the convergence parameters influ- geometry reconstruction of the human foot into enced by the contacts and hyper-elastic material Comsol Multiphisics® 3.5a is investigated. properties. Comsol Multiphisics® offers a direct link with two of the most powerful commercial tools able Keywords: CT scan, CAD foot model, hyper- to generate 3D tetrahedral mesh models starting elastic material, contact analysis, plantar pressure from stack-up images: ScanFE® (by Simple- map. ware®) and Mimics® (by Materialise®) [11]. However, as reported and experimented yet in 1. Introduction [12], so-imported mesh models cannot be edited in Comsol Multiphisics®. This program, when It was reported that the perceived comfort working on tessellated geometries, creates ra- related to the human foot can be associated to the tional Bezier patches, defining boundary or do- contact pressure generated at the plantar - insole main equations. Manipulating or editing those interface [1]. High values of pressure can gener- boundaries/domains, which requires geometry ate pain or pathologies due to the obstruction of decomposition analysis, is not allowed. blood circulation in areas with peak values of To avoid all these crucial issues, one should pressure. Experimental studies have pointed out create B-rep CAD geometry starting from seg- a relationship between perceived comfort and mented surfaces, extracted from stack-up images. plantar pressures [2], [3]. Over years, many re- If, on one hand, this stage may be time consum- searchers have addressed their attention on ing, on the other hand a suitable CAD geometry minimizing the plantar pressure, by varying in- model is finally available and ready to be post- sole footwear materials, thickness and anatomi- processed into any multiphysic simulation. cal shape [4], [5], [6]. The above approach was adopted, for exam- Recently, in order to give a valuable support ple, into [13], where, starting from MR scans, the to experimental investigations, computational foot geometry was created and then assembled into SolidWorks® CAD system. CAD model, the FE model was created directly In the present paper, the development of the into Comsol Multiphisics® for the non-linear detailed 3D anatomic FE model of a human foot analysis, by using the live-link between both is described. The balanced standing condition environments. Boundary conditions, contact and was simulated: the foot was supposed to be identity pairs were introduced. Domain equations touching an ideal-rigid ground. Hyper-elastic were set to simulate the non-linear hyper-elastic material law was assigned to soft tissues. Contact behavior of the foot soft tissue. pressures were calculated by adopting a non- linear static simulation. How to speed-up the 3. Foot Modeling solution convergence by fine-tuning non-linear tolerance, penalty factor and scaling value, was A CT (Toshiba® Aquilion 4 equipment) scan also highlighted. was performed on a 29 years old male (65 Kg). 345 slices were captured with a slice distance of 2. Methodology Overview 1.0 mm (see Figure 2.a). Scans were made for both feet in their neutral Figure 1 depicts the general work-flow posture in which there is the least tension or adopted in the present research. pressure on tendons, muscles and bones. Foot CT scan images .DICOM format (Toshiba® Aquilion 4) 3D Image reconstruction .STL format (ScanIP® module 3.2) Figure 2.a. DICOM image CAD modeling live-link (SolidWorks® 2010) FE modeling (Comsol Multiphysics® 3.5a) 2D segmented regions 3D reconstructed domains Figure 2.b. Segmented regions and 3D reconstruction Figure 1. Work-flow methodology Medical images were, then, exported into A 29 years old male was submitted to a CT standard .DICOM format (image resolution scan. Medical images of both feet were imported 512x512 pixels) and processed by using into ScanIP® module of Simplewere® software, ScanIP® tools. Generally speaking, DICOM where bones and soft tissues were extracted by images are gray-based images. Different gray- adopting density-based segmentation procedures. levels correspond to different density materials At this stage boundary surfaces, into the tessel- (Figure 2.b). Looking at DICOM images the lated format, were generated. Those surfaces following regions can be distinguished: soft tis- were, then, exported into .STL format and im- sue, bone, ligaments, plantar fascia and carti- ported into SolidWorks® CAD system. Here, lages. In the present paper, only bones and soft solid domains were generated by adopting tissue were segmented. Ligaments and plantar loft/sweep and boolean operations. From this fascia were added at FEM stage as equivalent load conditions (see also Section 4); instead, lated surfaces), lofting/sweeping/filling surfaces cartilages were modeled separately at CAD were generated as also described in [14]. stage. In order to reduce the reconstruction ef- Figure 4 shows the typical work-flow (first fort, slice pixels related to left foot were re- metatarsal bone used as example) adopted to moved. Thus, in the following only the right foot generate solid domains, starting from cross- will be analyzed. section curves. Figures 3.a and 3.b show the assembled bone CAD procedure is based on the following structure and the soft tissue domain as seen into criteria: ScanIP® environment, respectively. Bone struc- • minimum number of surface patches; and, ture was composed of 19 bones: tibia, fibula, • surface patches large as much as possible. talus, calcaneus, cuboid, navicular, 3 cuneiforms All this assures more flexibility in handling 3D (bones of the metatarsus), 5 metatarsals (bones mesh and boundary conditions at FEM stage. of the metatarsus) and 5 components of the pha- langes (bones of the toes). Phalange bones (a proximal and a distal phalanx for the great toe; proximal, middle and distal phalanges for the second to fifth toes) were fused together since their relative motion do not affect plantar pres- sures. a. Bone structure b. Soft tissue Figure 5. 3D CAD domains generated into SolidWorks® Figure 5 depicts the so-reconstructed CAD geometry. Cartilages that were not extracted into a. Bone structure b. Soft tissue the segmentation phase were then modeled into Figure 3. Tessellated surfaces generated the CAD system in order to joint bones and fill into ScanIP® environment the cartilaginous space (see Figure 5.a). Boolean operations were used to ensure congruence One should note that the so-generated do- among the related interfacial surfaces. For in- mains are geometrically described by the tessel- stance, the whole bone structure was subtracted lated boundary surfaces. from the soft tissue. Finally, toes at soft tissue These tessellated models were then imported level were merged together (Figure 5.b). into SolidWorks® CAD system by using the SCANto3D® add-in module to process and fixed boundary (UFS) manage imported tessellated surfaces. y x z a b c Figure 4. Generation of CAD model. a: tessellated geometry; b: cross-section curves; c: 3D CAD model ground Starting from cross-sections (created as inter- section curves between cut planes and the tessel- Figure 6. FE model as seen into Comsol Multiphisics® 4. FE Modeling Constant Value Ebone (MPa) 7300.0 The foot CAD model was thus imported into Ecartilage (MPa) 10.0 ν Comsol Multiphisics® 3.5a, by using the live- bone 0.30 ν link connection with SolidWorks®. cartilage 0.40 Here, domain equations, boundary conditions Table 2. Material constants for bones and cartilages [7] and solver settings were provided. In the present paper the balanced standing 4.2 Boundary Conditions condition was simulated. The foot was supposed to touch an ideal-rigid flat ground. For this pur- During the balanced standing condition, a pose the “ground” domain was added to the FE vertical force, corresponding to one half of the model (see Figure 6). body weight (F =650/2 N), is transferred from w the body to the foot and then to the ground. 4.1 Domain Equations The plantar fascia stabilizes the longitudinal arch of the foot and supports the longitudinal Materials were assumed linear and isotropic, forces during the weight application phase [8].
Recommended publications
  • Management of Large Sets of Image Data Capture, Databases, Image Processing, Storage, Visualization Karol Kozak
    Management of large sets of image data Capture, Databases, Image Processing, Storage, Visualization Karol Kozak Download free books at Karol Kozak Management of large sets of image data Capture, Databases, Image Processing, Storage, Visualization Download free eBooks at bookboon.com 2 Management of large sets of image data: Capture, Databases, Image Processing, Storage, Visualization 1st edition © 2014 Karol Kozak & bookboon.com ISBN 978-87-403-0726-9 Download free eBooks at bookboon.com 3 Management of large sets of image data Contents Contents 1 Digital image 6 2 History of digital imaging 10 3 Amount of produced images – is it danger? 18 4 Digital image and privacy 20 5 Digital cameras 27 5.1 Methods of image capture 31 6 Image formats 33 7 Image Metadata – data about data 39 8 Interactive visualization (IV) 44 9 Basic of image processing 49 Download free eBooks at bookboon.com 4 Click on the ad to read more Management of large sets of image data Contents 10 Image Processing software 62 11 Image management and image databases 79 12 Operating system (os) and images 97 13 Graphics processing unit (GPU) 100 14 Storage and archive 101 15 Images in different disciplines 109 15.1 Microscopy 109 360° 15.2 Medical imaging 114 15.3 Astronomical images 117 15.4 Industrial imaging 360° 118 thinking. 16 Selection of best digital images 120 References: thinking. 124 360° thinking . 360° thinking. Discover the truth at www.deloitte.ca/careers Discover the truth at www.deloitte.ca/careers © Deloitte & Touche LLP and affiliated entities. Discover the truth at www.deloitte.ca/careers © Deloitte & Touche LLP and affiliated entities.
    [Show full text]
  • Simpleware Scanip Medical Software Solutions for Clinical Applications
    Simpleware ScanIP Medical Software Solutions for Clinical Applications FDA 510(k) cleared CE marked ISO 13485:2016 certified Software Solutions for Clinical Applications Patient-Specific Surgical Planning Patient-Specific Design Improve Informed Decision- Accelerate New Product Making Development • Generate models from 3D image data to visualize • Import, position and integrate CAD devices into patient treatment options image data • Landmark and perform measurements on anatomical • Reverse engineer and analyse patient-specific data to assess surgical strategies device designs • Export models for simulating clinical procedures • Generate simulation-ready models for evaluating device performance In Silico Clinical Trials R&D for Medical Devices Increase Confidence in Your Harness the Freedom to Solution Experiment • Explore post-op outcomes or implant positioning or • Generate accurate models for 3D printing, simulation or device performance CAD design • Fast and accurate image processing environment for • Speed up iterative device designs with rapid image-to- creating computational models model workflows • Streamline repeatable workflows with scripting, • Use image-based tools to reduce dependence on automation, or customization physical testing 3D Image Data Processing for Pre-Clinical Applications with Simpleware ScanIP Medical Intuitive and Powerful Software Tackle Clinical Imaging Challenges with Confidence When working in a clinical setting, Simpleware ScanIP Medical is the ideal choice for those working with 3D imaging to create medical
    [Show full text]
  • Simpleware LTD. Ə Dr. Gareth James Marketing and PR Officer Bradninch
    DEPARTMENT OF HEALTH & HUMAN SERVICES Public Health Service __________________________________________________________________________________________________________________________ Food and Drug Administration 10903 New Hampshire Avenue Document Control Center – WO66-G609 Silver Spring, MD 20993-0002 Simpleware LTD. April 17, 2015 Ə Dr. Gareth James Marketing and PR Officer Bradninch Hall Castle Street EXETER, GB EX43PL DEVON Re: K142779 Trade/Device Name: ScanIP; ScanIP: Medical Edition; ScanIP: Med Regulation Number: 21 CFR 892.2050 Regulation Name: Picture Archiving and Communications System Regulatory Class: II Product Code: LLZ Dated: March 19, 2015 Received: March 25, 2015 Dear Dr. James: We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading. If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls.
    [Show full text]
  • Hands-On Engineering Courses in the COVID-19 Pandemic: Adapting Medical Device Design for Remote Learning
    Physical and Engineering Sciences in Medicine https://doi.org/10.1007/s13246-020-00967-z SCIENTIFIC PAPER Hands-on engineering courses in the COVID-19 pandemic: adapting medical device design for remote learning Yanning Liu1 · Aishwarya Vijay2 · Steven M. Tommasini1,3 · Daniel Wiznia3,4,5 Received: 1 September 2020 / Accepted: 18 December 2020 © Australasian College of Physical Scientists and Engineers in Medicine 2021 Abstract The COVID-19 pandemic has challenged the status quo of engineering education, especially in highly interactive, hands-on design classes. Here, we present an example of how we efectively adjusted an intensive hands-on, group project-based engi- neering course, Medical Device Design & Innovation, to a remote learning curriculum. We frst describe the modifcations we made. Drawing from student pre and post feedback surveys and our observations, we conclude that our adaptations were overall successful. Our experience may guide educators who are transitioning their engineering design courses to remote learning. Keywords COVID-19 · Engineering education · Remote learning · STEM · Product design · Medical device design Introduction how we efectively adjusted an intensive hands-on, group project-based engineering course, Medical Device Design The COVID-19 pandemic has challenged the status quo and Innovation.[4]. of engineering education, especially in highly interactive, Medical Device Design and Innovation is a project hands-on design classes.[1, 2] Traditionally, these classes focused course ofered to all Yale University
    [Show full text]
  • Sergey Makarov
    Sergey Makarov · Marc Horner Gregory Noetscher Editors Brain and Human Body Modeling Computational Human Modeling at EMBC 2018 Brain and Human Body Modeling Sergey Makarov • Marc Horner Gregory Noetscher Editors Brain and Human Body Modeling Computational Human Modeling at EMBC 2018 Editors Sergey Makarov Marc Horner Massachusetts General Hospital ANSYS, Inc. Boston, MA, USA Evanston, IL, USA Worcester Polytechnic Institute Worcester, MA, USA Gregory Noetscher Worcester Polytechnic Institute Worcester, MA, USA This book is an open access publication. ISBN 978-3-030-21292-6 ISBN 978-3-030-21293-3 (eBook) https://doi.org/10.1007/978-3-030-21293-3 © The Editor(s) (if applicable) and The Author(s) 2019 Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this book are included in the book’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
    [Show full text]
  • Simpleware Software Solutions for Life Sciences from 3D Images to Models Applications in Life Sciences
    Simpleware Software Solutions for Life Sciences From 3D Images to Models Applications in Life Sciences Orthopedics Product Design & Analysis Cardio & Respiratory Systems Accurate Anatomical Consumer Products Physiological Flow Models and Wearables Analysis • Automated and semi-automated • Customize product designs to • Reslice images along vessels tools to segment anatomies individual anatomies and airways • Combine CAD implants and • Virtually check the fit and • Combine anatomical data with anatomical data function for devices including stent models • Accurately quantify bone electronic wearables • Mesh boundary layers and add geometries • Export models to simulate real- custom inlets and outlets for • Export multi-part FE/CFD world performance fluid flow analysis meshes to solvers • Gain better insight for future • Quantify vessels with centerline products by analyzing network tools real anatomies EM & Neuromodulation Medical Device R&D Anatomical 3D Printing Human Body Models Device and Image High-Quality STL for Simulation Integration Production • Use automated and/or semi- • Rapidly integrate CAD devices into • Print medical devices and automated segmentation tools CT/MRI scans anatomical parts from scans • Integrate CAD designs like MRI • Research human/device • Generate robust STL files ready coils or electrodes with image data interactions for 3D printing • Easy-to-use registration tools for • Automate repeatable operations • Conforming interfaces for multi- positioning devices with scripting material printing • Generate and export
    [Show full text]
  • An Open-Source, Fully-Automated, Realistic Volumetric-Approach-Based Simulator for TES*
    ROAST: an open-source, fully-automated, Realistic vOlumetric-Approach-based Simulator for TES* Yu Huang1;2, Abhishek Datta2, Marom Bikson1 and Lucas C. Parra1 Abstract— Research in the area of transcranial electrical Providence, RI), COMSOL Multiphysics (COMSOL Inc., stimulation (TES) often relies on computational models of cur- Burlington, MA)). rent flow in the brain. Models are built on magnetic resonance Given this great variety and complexity, there is a need images (MRI) of the human head to capture detailed individual anatomy. To simulate current flow, MRIs have to be segmented, to automate these tools into a complete processing pipeline. virtual electrodes have to be placed on the scalp, the volume is Existing pipelines are either not fully automated (e.g. NFT tessellated into a mesh, and the finite element model is solved [11]) or difficult to use (e.g. SciRun [12]). Notable in numerically to estimate the current flow. Various software tools terms of ease of use (if not of installation) is SimNIBS are available for each step, as well as processing pipelines [13], which integrates FreeSurfer, FSL, Gmsh and getDP to that connect these tools for automated or semi-automated processing. The goal of the present tool – ROAST – is to provide provide a complete end-to-end solution, based on the surface an end-to-end pipeline that can automatically process individual segmentation of the head. In the TES modeling literature, heads with realistic volumetric anatomy leveraging open-source however, FEM based on volumetric segmentation is preferred software (SPM8, iso2mesh and getDP) and custom scripts over boundary element method (BEM) that is more common to improve segmentation and execute electrode placement.
    [Show full text]
  • PLM Industry Summary Jillian Hayes, Editor Vol
    PLM Industry Summary Jillian Hayes, Editor Vol. 16 No. 49 Friday 5 December 2014 Contents CIMdata News _____________________________________________________________________ 2 CIMdata Publishes PLM Industry Report ____________________________________________________2 CIMdata Releases Series of Country-Specific PLM Market Analysis Reports ________________________5 A New Business Calculus from IBM Software Group ___________________________________________6 SmarTeam: Offering Users Options for Growth: a CIMdata Commentary __________________________10 Subscribing to Product Design Software: a CIMdata Commentary ________________________________12 Company News ____________________________________________________________________ 14 3D Systems Makes Forbes’ List of America’s Best 100 Small Companies __________________________14 Adris, MicroCAD and Graitec UK become one Company Graitec Limited _________________________14 ASCENT- Center for Technical Knowledge Announces Plans to Collaborate with 4D Technologies on Training and Learning Resources for Autodesk Software Users __________________________________15 Autodesk Makes Design Software Free to Schools Worldwide ___________________________________16 Brian Beattie Named EVP, Business Operations and Chief Administrative Officer ___________________17 Cimatron Donates $1.7 Million Software to Iowa Community College for Advanced CAD/CAM Training 18 Dassault Systèmes and Expo Milano 2015: Partners to Promote Eco-Sustainability Exhibition __________18 ESI and EDF Energies Nouvelles sign an Exclusive
    [Show full text]
  • Synopsys (Northern Europe) Ltd
    Synopsys (Northern Europe) Ltd. April 1, 2021 ℅ Ms. Jessica James Business Process Analyst Bradninch Hall, Castle Street Exeter, Devon EX4 3PL UNITED KINGDOM Re: K203195 Trade/Device Name: Simpleware ScanIP Medical Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ Dated: October 26, 2020 Received: October 28, 2020 Dear Ms. James: We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
    [Show full text]
  • Multiphysics Software Applications in Reverse Engineering
    Multiphysics Software Applications in Reverse Engineering *W. Wang1, K. Genc2 1University of Massachusetts Lowell, Lowell, MA, USA 2Simpleware, Exeter, United Kingdom *Corresponding author: University of Massachusetts Lowell, One University Avenue, Lowell, MA 01854, USA. [email protected] Abstract: This paper will explore the segmented geometry that can be directly applications of advanced software such as imported into the COMSOL environment. An ScanIP and the +FE module (Simpleware Ltd., overview of the workflow steps are shown in Exeter UK) and COMSOL multiphysics Figure 1. The COMSOL multiphysics software software in reinventing an existing part in the environment is capable of facilitating all steps in absence of original design data. It showcases the the modeling and simulation processes from part reverse engineering workflow of going from a definining, feature based meshing to 3D computed tomography (CT) scan of an visualization and solution analysis. However, automotive engine manifold to a COMSOL this paper aims at the demonstration of simulation ready, multi-part computational fluid integration of Simpleware and COMSOL in dynamics (CFD) or finite element (FE) mesh of reverse engineering applications, and we will the segmented geometry. It discusses the focus on the first three steps (blue), which effectiveness of applying multiphysics software describe the workflow of generating a in reverse engineering practice with a focus on simulation-ready mesh from 3D images using the the applicability of Simpleware and COMSOL in ScanIP+FE softrware environment. three-dimensional (3D) image-based modeling, structure analysis and functionality evaluation. Keywords: Reverse Engineering, 3D Image- Based Simulation, Computational Fluid Dynamics, Finite Element 1. Introduction Figure1. Overview of the 3D image-based reverse During the past decade reverse engineering engineering workflow.
    [Show full text]
  • Feature Comparison of Simpleware Software Products Version Q-2020.06
    DATASHEET Feature Comparison of Simpleware Software Products Version Q-2020.06 Image Processing Software Options Feature Simpleware ScanIP Simpleware ScanIP Medical Import Image Data (incl. CT, MRI, Jpeg…) Store, Manage, and Anonymize DICOM tags Register Multiple Datasets Image Processing Tools (Crop, Resample, Align…) Volume Rendering Segmentation Image Space Filters for Artefact Removal and Correction Robust Booleans Between Parts Measurement and Statistics Tools Shape Fitting and Stats Wall Thickness Analysis Generate and Probe Centerline Networks Generate High Quality Surface Meshes Export Single or Multi-Part STL Files Export Range of Suface Formats CE Marked and FDA (510k) Cleared Connect to PACS for Image Retrieval Import 4D DICOM Import and Register 2D X-Ray Images Generate Virtual X-Rays Export Encrypted 3D PDF Files Scripting API (C#, Python)* synopsys.com/simpleware Add-On Modules Automated Segmentation CAD Integration Model Generation Physics Simulation AS AS Custom Design Feature CAD FE NURBS SOLID FLOW LAPLACE Cardio Ortho Modeler Link Fully Automated Segmentation of Hearts Automatic Placement of Anatomical Landmarks for Hearts Fully Automated Segmentation of Hips and Knees Automatic Placement of Anatomical Landmarks for Hips and Knees Automatic Region of Interest Detection for Auto Segmentation Fully Customized Automated Image Processing Solution Import Surface Objects (STL, STEP, IGES…) Check and Fix Surface Objects Create Primitive Shapes Register Datasets (Automatic, Landmark…) Position Surface Objects Surface Filters (Smooth, Decimate…) Surface Editing (Extrude, Clip, Hollow, Sweep…) Convert Surfaces to Masks, Masks to Surfaces Robust Booleans Between Surface Parts Surface Deviation Feature Edge Preservation Internal Structures Wizard Mesh Decimation and Refinement Options Export STL Files Import SOLIDWORKS® Parts or Assemblies Dynamic Link with SOLIDWORKS® (Pull, Position, Orientation...) 2 Add-On Modules Cont.
    [Show full text]
  • 2017 Abstract Book Ionized and Molecular Gas in IC 860: Evidence for an Outflow Carson Adams Mentors: Katherine Alatalo and Anne M
    2017 Abstract Book Ionized and Molecular Gas in IC 860: Evidence for an Outflow Carson Adams Mentors: Katherine Alatalo and Anne M. Medling Galaxies at present-day fall predominantly in two distinct populations, as either blue, star-forming spirals or red, quiescent early-type galaxies. Blue galaxies appear to evolve onto the red sequence as star formation is quenched. The absence of a significant population falling in the intermediate ‘green valley’ implies that these transitions must occur rapidly. Identifying the initial properties of and pathways taken by these ‘dying galaxies’ is essential to building a complete understanding of galactic evolution. In this work, we investigate these phenomena in action within IC 860 — a nearby, early-type spiral in the initial stages of undergoing a rapid transition in the presence of a powerful AGN-driven molecular outflow. As a shocked, post-starburst galaxy with an intermediate-age stellar population which lies on the blue end of the green valley, IC 860 provides a window into the early stages of galaxy transition and AGN feedback. We present Hubble Space Telescope imaging of IC 860 showing a violent, dusty outflow originating from a compact core. We find that the mean velocity map of the CO(1-0) from CARMA suggests a dynamically excited bar funneling molecular gas into the galactic center. Finally, we present kinematic maps of ionized gas emission lines as well as sodium D absorption tracing neutral winds obtained by the Wide-Field Spectrograph. Moving Mass and Mechanical Clutch Mechanisms for One-Dimensional Hopping Robots Sara Adams Mentors: Aaron Ames and Eric Ambrose There are a number of potential mechanisms to create a hopping motion in robots, but not many are energy efficient.
    [Show full text]