Management of Large Sets of Image Data Capture, Databases, Image Processing, Storage, Visualization
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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. -
Road Lane Detection for Android
MASARYK UNIVERSITY FACULTY}w¡¢£¤¥¦§¨ OF I !"#$%&'()+,-./012345<yA|NFORMATICS Road lane detection for Android BACHELOR THESIS Jakub Medvecký-Heretik Brno, spring 2014 Declaration I do hereby declare, that this paper is my original authorial work, which I have worked on by my own. All sources, references and liter- ature used or excerpted during elaboration of this work are properly cited and listed in complete reference to the due source. Jakub Medvecký-Heretik Advisor: Mgr. Dušan Klinec Acknowledgement I would like to thank my supervisor, Mgr. Dušan Klinec for his con- tinual support and advice throughout this work. I would also like to thank my family and friends for their support. Abstract The aim of this bachelor thesis was to analyze the possibilities of im- age processing techniques on the Android mobile platform for the purposes of a computer vision application focusing on the problem of road lane detection. Utilizing the results of the analysis an appli- cation was created, which detects lines and circles in an image in real time using various approaches to segmentation and different imple- mentations of the Hough transform. The application makes use of the OpenCV library and the results achieved with its help are com- pared to the results achieved with my own implementation. Keywords computer vision, road lane detection, circle detection, image process- ing, segmentation, Android, OpenCV, Hough transform Contents 1 Introduction ............................ 3 2 Computer vision ......................... 5 2.1 Image processing ...................... 5 2.2 Techniques .......................... 6 2.3 Existing libraries ...................... 6 2.3.1 OpenCV . 6 2.3.2 VXL . 7 2.3.3 ImageJ . -
Survey of Databases Used in Image Processing and Their Applications
International Journal of Scientific & Engineering Research Volume 2, Issue 10, Oct-2011 1 ISSN 2229-5518 Survey of Databases Used in Image Processing and Their Applications Shubhpreet Kaur, Gagandeep Jindal Abstract- This paper gives review of Medical image database (MIDB) systems which have been developed in the past few years for research for medical fraternity and students. In this paper, I have surveyed all available medical image databases relevant for research and their use. Keywords: Image database, Medical Image Database System. —————————— —————————— 1. INTRODUCTION Measurement and recording techniques, such as electroencephalography, magnetoencephalography Medical imaging is the technique and process used to (MEG), Electrocardiography (EKG) and others, can create images of the human for clinical purposes be seen as forms of medical imaging. Image Analysis (medical procedures seeking to reveal, diagnose or is done to ensure database consistency and reliable examine disease) or medical science. As a discipline, image processing. it is part of biological imaging and incorporates radiology, nuclear medicine, investigative Open source software for medical image analysis radiological sciences, endoscopy, (medical) Several open source software packages are available thermography, medical photography and for performing analysis of medical images: microscopy. ImageJ 3D Slicer ITK Shubhpreet Kaur is currently pursuing masters degree OsiriX program in Computer Science and engineering in GemIdent Chandigarh Engineering College, Mohali, India. E-mail: MicroDicom [email protected] FreeSurfer Gagandeep Jindal is currently assistant processor in 1.1 Images used in Medical Research department Computer Science and Engineering in Here is the description of various modalities that are Chandigarh Engineering College, Mohali, India. E-mail: used for the purpose of research by medical and [email protected] engineering students as well as doctors. -
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 -
Automated Malware Analysis Report for Microdicom-3.0.1
ID: 153765 Sample Name: MicroDicom- 3.0.1-x64.exe Cookbook: default.jbs Time: 13:55:16 Date: 18/07/2019 Version: 26.0.0 Aquamarine Table of Contents Table of Contents 2 Analysis Report MicroDicom-3.0.1-x64.exe 4 Overview 4 General Information 4 Detection 4 Confidence 5 Classification 5 Analysis Advice 5 Mitre Att&ck Matrix 6 Signature Overview 6 AV Detection: 6 Spreading: 6 Networking: 6 Key, Mouse, Clipboard, Microphone and Screen Capturing: 6 System Summary: 7 Data Obfuscation: 7 Persistence and Installation Behavior: 7 Boot Survival: 7 Hooking and other Techniques for Hiding and Protection: 7 Malware Analysis System Evasion: 7 Anti Debugging: 8 HIPS / PFW / Operating System Protection Evasion: 8 Language, Device and Operating System Detection: 8 Behavior Graph 8 Simulations 8 Behavior and APIs 8 Antivirus and Machine Learning Detection 9 Initial Sample 9 Dropped Files 9 Unpacked PE Files 9 Domains 9 URLs 9 Yara Overview 9 Initial Sample 9 PCAP (Network Traffic) 9 Dropped Files 9 Memory Dumps 9 Unpacked PEs 9 Joe Sandbox View / Context 10 IPs 10 Domains 10 ASN 10 JA3 Fingerprints 10 Dropped Files 10 Screenshots 10 Thumbnails 10 Startup 11 Created / dropped Files 11 Domains and IPs 17 Contacted Domains 17 URLs from Memory and Binaries 17 Contacted IPs 17 Static File Info 17 General 18 File Icon 18 Static PE Info 18 General 18 Entrypoint Preview 18 Rich Headers 19 Copyright Joe Security LLC 2019 Page 2 of 44 Data Directories 19 Sections 20 Resources 20 Imports 20 Possible Origin 21 Network Behavior 21 Code Manipulations 21 Statistics 21 -
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. -
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 -
Schmidt BT 2020.Pdf
FRIEDRICH-ALEXANDER-UNIVERSITÄT ERLANGEN-NÜRNBERG TECHNISCHE FAKULTÄT • DEPARTMENT INFORMATIK Lehrstuhl für Informatik 10 (Systemsimulation) Investigation and Implementation of Visualization and Reconstruction Options for Breast-CT Simon Schmidt Bachelorthesis Investigation and Implementation of Visualization and Reconstruction Options for Breast-CT Simon Schmidt Bachelorthesis Aufgabensteller: Prof. Dr.-Ing. Harald Köstler Betreuer: Dr. David Heinemann (AB-CT) Bearbeitungszeitraum: 1.6.2020 – 2.11.2020 Erklärung: Ich versichere, dass ich die Arbeit ohne fremde Hilfe und ohne Benutzung anderer als der angegebenen Quellen angefertigt habe und dass die Arbeit in gleicher oder ähn- licher Form noch keiner anderen Prüfungsbehörde vorgelegen hat und von dieser als Teil einer Prüfungsleistung angenommen wurde. Alle Ausführungen, die wörtlich oder sinngemäß übernommen wurden, sind als solche gekennzeichnet. Der Universität Erlangen-Nürnberg, vertreten durch den Lehrstuhl für Systemsimulati- on (Informatik 10), wird für Zwecke der Forschung und Lehre ein einfaches, kostenloses, zeitlich und örtlich unbeschränktes Nutzungsrecht an den Arbeitsergebnissen der Ba- chelorthesis einschließlich etwaiger Schutzrechte und Urheberrechte eingeräumt. Erlangen, den 1. November 2020 . Abstract The nu:view Breast-CT is the worlds first spiral Breast-CT. While already in clinical use, the system is still under on-going development. In the current clinical workflow, the acquired scans have to be reconstructed and then transferred to the clinical network before they can be reviewed on a workstation in another room. As the necessary amount of data for a single scan is huge, this can take long times. The goal of this thesis was therefore, to improve on those weak points by investigating viewing options which could be used in close proximity to the scanner. -
André Vilas Boas Da Costa Retscan: Efficient Fovea and Optic Disc Detection in Retinographies
Universidade do Minho Escola de Engenharia André Vilas Boas da Costa RetScan: Efficient Fovea and Optic Disc Detection in Retinographies Outubro de 2011 Universidade do Minho Escola de Engenharia Departamento de Informática André Vilas Boas da Costa RetScan: Efficient Fovea and Optic Disc Detection in Retinographies Dissertação de Mestrado Mestrado de Informática Trabalho realizado sob orientação de Alberto José Proença Outubro de 2011 Abstract The Fovea and Optic Disc are relevant anatomical eye structures to diagnose var- ious diseases. Its automatic detection can provide both a cost reduction when analysing large populations and improve the effectiveness of ophthalmologists and optometrists. This dissertation describes a methodology to automatically detect these structures and analyses a, CPU only, MATLAB implementation of this methodology. RetScan is a port to a freeware environment of this methodology, its functionality and perfor- mance are evaluated and compared to the original. The results of both evaluations lead to a discussion on possible improvements in the metodology that influence the functionality and performance. The resulting improvements are implemented and integrated in RetScan. To further improve performance, a parallelization of RetScan to take advantage of a multi-core architecture or a CUDA-enabled accelerator was designed, coded and evaluated. This evaluation reveals that RetScan achieves its best throughput efficiency using a multi-core architecture only and analysing several images at once. For one image usage, using multi-core only is also the best solution, but with a small speed-up. The usage of CUDA-enabled accelerators is not recom- mended for this scope as the images are small and the cost of the data transfer to and from the accelerator has a severe impact on performance. -
Vendor Questions and Answers
COMMUNITY COLLEGE OF ALLEGHENY COUNTY PURCHASING DEPARTMENT 800 ALLEGHENY AVENUE, PITTSBURGH, PA 15233 ADDENDUM 1 REQUEST FOR PROPOSAL 3104 NETWORK ACCESS CONTROL SOLUTION APRIL 10, 2018 The following additional information is hereby made a part of this RFP: **************************************************************************** See the accompanying vendor compliance matrix. See accompanying “Addendum A” (partial listing of network devices and protocols/services/applications that NAC solution must support). The protocols include listing from the current RFPs’ appendixes. It should be noted this is not an all-inclusive list, the chosen NAC solution should support all standard protocols or provide explanation of non- support. See accompanying Addendum B - Partial listing existing desktop and server software applciartions (referred to in questions 27 on page 9 of the RFP). “Addendum C” – listing of existing college network equipment Vendor Questions and Answers: 1. What is the VPN Gateway technology being used? (sec 2.1) Fortinet FortiGate 2. Can further clarifications be made regarding "specific settings to the endpoint to operate." be identified? Is the provisioning of administrative accounts per host impacted by this function? (Section 3.1 statement 7) It is desired that the proposed NAC solution should not require or expect any specific setting or component on the end-user system to be exist or configured in order the NAC solution to provide all its functionality. If the NAC solution requires certain software component(s) to exist on the end user systems, the vendors must provide detailed information about their proposed system and how it would function in the college’s environment. 3. Please elaborate on what "relevant information" refers to, respective to information being shared with other college systems. -
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. -
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