Verification and Validation of an Open Source–Based Morphology Analysis Platform to Support Implant Design

2013 ◽  
Vol 7 (4) ◽  
Author(s):  
Jeffrey E. Bischoff ◽  
Brad Davis ◽  
Jörn Seebeck ◽  
Adam Henderson ◽  
Joel Zuhars ◽  
...  
Keyword(s):  
Open Source ◽  
Image Data ◽  
Verification And Validation ◽  
Implant Design ◽  
Essential Requirement ◽  
Medical Device Design ◽  
Device Development ◽  
Commercial Code ◽  
Modeling Techniques ◽  
Analysis Platform

Availability of medical image data and ongoing advancement of image-processing and mathematical-modeling techniques are increasingly enabling device manufacturers to conduct clinically relevant morphological and mechanical analyses across populations to support device development. Gaps in the ability of contemporary commercial codes to fully realize these analytical goals frequently requires some amount of in-house code development and deployment. Verification and validation (V&V) of these custom modules or platforms is an essential requirement for deployment of the software within a medical device design controls system. One such software platform to support orthopedic morphological analysis, zibra, has been successfully developed through a collaborative relationship between Zimmer, Inc. and Kitware, Inc. The development process involved configuration of commercial code, open-source toolkits, and custom code. Here, the V&V strategy to support deployment of zibra is described.

scholarly journals GRACETOOLS—GRACE Gravity Field Recovery Tools

Geosciences ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 350 ◽  
Author(s):  
Neda Darbeheshti ◽  
Florian Wöske ◽  
Matthias Weigelt ◽  
Christopher Mccullough ◽  
Hu Wu
Keyword(s):  
Open Source ◽  
Gravity Field ◽  
Transition Matrix ◽  
State Transition ◽  
Satellite Observations ◽  
Gravity Field Recovery ◽  
Grace Data ◽  
Range Rate ◽  
Analysis Platform ◽  
Recovery Tools

This paper introduces GRACETOOLS, the first open source gravity field recovery tool using GRACE type satellite observations. Our aim is to initiate an open source GRACE data analysis platform, where the existing algorithms and codes for working with GRACE data are shared and improved. We describe the first release of GRACETOOLS that includes solving variational equations for gravity field recovery using GRACE range rate observations. All mathematical models are presented in a matrix format, with emphasis on state transition matrix, followed by details of the batch least squares algorithm. At the end, we demonstrate how GRACETOOLS works with simulated GRACE type observations. The first release of GRACETOOLS consist of all MATLAB M-files and is publicly available at Supplementary Materials.

Comparative analysis on flow over cylinder between commercial code and open source algorithm

2017 ◽  
Author(s):  
Zulaikha Asyiqin Nur Azri ◽  
Ishkrizat Taib ◽  
Azmahani Sadikin ◽  
Muhammad Sufyan Amir Paisal ◽  
Akmal Nizam Mohammed ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Open Source ◽  
Commercial Code ◽  
Flow Over Cylinder

Biomass Ground Segment Architecture, Multi-Mission Algorithm and Analysis Platform (MAAP) and Related Open-Source Developments

2021 ◽  
Author(s):  
Clement Albinet ◽  
Stefanie Lumnitz ◽  
Bjorn Frommknech ◽  
Nuno Miranda ◽  
Klaus Scioal ◽  
...  
Keyword(s):  
Open Source ◽  
Ground Segment ◽  
Analysis Platform

A Detailed Five-Year Review of Medical Device Additive Manufacturing Research and its Potential for Translation to Clinical Practice

2015 ◽  
Author(s):  
Katherine Stephenson
Keyword(s):  
Systematic Review ◽  
Clinical Practice ◽  
Additive Manufacturing ◽  
3D Printing ◽  
Medical Device ◽  
Development Stage ◽  
Medical Device Design ◽  
Device Development ◽  
Near Term ◽  
Common Clinical Practice

This paper provides a systematic review of over 350 publications that document specific medical device examples in which the design and manufacturing relied on additive manufacturing processes (more popularly referred to as “3d Printing”). Existing reviews on 3d printing for medical device design focus on the range of clinical applications and potential uses for this technology. However, existing work tends to omit key medical device development and regulatory requirements pertaining to the use of 3d printing for technology translation. These omissions often present a skewed view of each device’s potential for rapid translation to commercialization and common clinical practice. To fill gaps in existing literature, this review includes medical device journal articles and identifies each article’s country of origin, the product development stage in which 3d printing was used, and the device’s specific type and classification under the U.S. Food and Drug Administration. The findings from this systematic review provide a detailed international snapshot of current additive manufacturing research and its near term potential for changing clinical practice.

scholarly journals VisBio: a Flexible Open-Source Visualization Package for Multidimensional Image Data

2006 ◽  
Vol 14 (3) ◽  
pp. 6-11
Author(s):  
Curtis T. Rueden ◽  
Kevin W. Eliceiri
Keyword(s):  
Open Source ◽  
Curve Fitting ◽  
Image Data ◽  
Time Lapse ◽  
Dramatic Improvement ◽  
Exponential Curve ◽  
Lifetime Imaging ◽  
The Past ◽  
Resultant Data ◽  
Fitting Algorithm

Over the past few years there has been a dramatic improvement in microscopy acquisition techniques, in effective imaging modalities as well as raw hardware performance. As the microscopist's available tools become more sophisticated and diverse—e.g., time-lapse, Z sectioning, multispectra, lifetime, nth harmonic, polarization, and many combinations thereof—we face a corresponding increase in complexity in the software for understanding and interpreting the resultant data. With lifetime imaging, for example, it is overwhelming to study the raw numbers; instead, an exponential curve-fitting algorithm must be applied to extract meaningful lifetime values from the mass of photon counts recorded by the instrument.

scholarly journals GeoChronR – an R package to model, analyze and visualize age-uncertain paleoscientific data

2020 ◽  
Author(s):  
Nicholas P. McKay ◽  
Julien Emile-Geay ◽  
Deborah Khider
Keyword(s):  
Open Source ◽  
Real World ◽  
Principal Component ◽  
R Package ◽  
Model Uncertainties ◽  
Data Standards ◽  
Spectral Analyses ◽  
Modeling Techniques ◽  
Age Model ◽  
The Impact

Abstract. Chronological uncertainty is a hallmark of the paleosciences. While many tools have been made available to researchers to quantify age uncertainties suitable for various settings and assumptions, disparate tools and output formats often discourage integrative approaches. In addition, associated tasks like propagating age model uncertainties to subsequent analyses, and visualizing the results, have received comparatively little attention in the literature and available software. Here we describe GeoChronR, an open-source R package to facilitate these tasks. GeoChronR is built around emerging data standards for the paleosciences (Linked PaleoData, or LiPD), and offers access to four popular age modeling techniques (Bacon, BChron, Oxcal, BAM). The output of these models is used to support ensemble-aware analyses, quantifying the impact of chronological uncertainties on common analyses like age-uncertain correlation, regression, principal component, and spectral analyses. We present five real-world use cases to illustrate how GeoChronR may be used to facilitate these tasks, to visualize the results in intuitive ways, and to store the results for further analysis, promoting transparency and reusability.

Efficient and scalable open-source JPIP server for streaming of large volumes of image data

2011 ◽  
Author(s):  
J.P. Garcia-Ortiz ◽  
C. Martin ◽  
V.G. Ruiz ◽  
J.J. Sanchez-Hernandez ◽  
I. Garcia ◽  
...  
Keyword(s):  
Open Source ◽  
Image Data

scholarly journals An Open Source, Extensible Malware Analysis Platform

2018 ◽  
Vol 188 ◽  
pp. 05009
Author(s):  
P. Michalopoulos ◽  
V. Ieronymakis ◽  
M.T. Khan ◽  
D. Serpanos
Keyword(s):  
Open Source ◽  
Malware Detection ◽  
High Rate ◽  
Machine Learning Techniques ◽  
False Alarms ◽  
Malware Analysis ◽  
Detection Techniques ◽  
It Systems ◽  
The One ◽  
Analysis Platform

A malware (such as viruses, ransomware) is the main source of bringing serious security threats to the IT systems and their users now-adays. In order to protect the systems and their legitimate users from these threats, anti-malware applications are developed as a defense against malware. However, most of these applications detect malware based on signatures or heuristics that are still created manually and are error prune. Some recent applications employ data mining and machine learning techniques to detect malware automatically. However, such applications fail to classify them appropriately mainly because they suffer from high rate of false alarms on the one hand and being retrospective, fail to detect new unknown threats and variants of known malware on the other hand. Since anti-malware vendors receive a huge number of malware samples every day, there is an urgent need for malware analysis tools that can automatically detect malware rigorously, i.e. eliminating false alarms. To address these issues and challenges of current malware detection and analysis approaches, we propose a novel, open source and extensible platform (based on set of tools) that allows to combine various malware detection techniques to automatically detect/classify a malware more rigorously. The developed platform can be fed with malware samples from different providers and will enable the development of effective classification schemes and methods, which are not sufficiently effective without collaboration and the related sample aggregation. Furthermore, such collaborative platforms in cybersecurity enable efficient sharing of information (e.g., about new identified threats) to all collaborators and sharing of appropriate defences against them, if such defences exist.

scholarly journals Introducing Biomedisa as an open-source online platform for biomedical image segmentation

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Philipp D. Lösel ◽  
Thomas van de Kamp ◽  
Alejandra Jayme ◽  
Alexey Ershov ◽  
Tomáš Faragó ◽  
...  
Keyword(s):  
Open Source ◽  
Automatic Segmentation ◽  
A Priori ◽  
Image Data ◽  
Training Data ◽  
Model Parameters ◽  
Web Browser ◽  
Online Platform ◽  
Biomedical Image ◽  
Volumetric Images

Abstract We present Biomedisa, a free and easy-to-use open-source online platform developed for semi-automatic segmentation of large volumetric images. The segmentation is based on a smart interpolation of sparsely pre-segmented slices taking into account the complete underlying image data. Biomedisa is particularly valuable when little a priori knowledge is available, e.g. for the dense annotation of the training data for a deep neural network. The platform is accessible through a web browser and requires no complex and tedious configuration of software and model parameters, thus addressing the needs of scientists without substantial computational expertise. We demonstrate that Biomedisa can drastically reduce both the time and human effort required to segment large images. It achieves a significant improvement over the conventional approach of densely pre-segmented slices with subsequent morphological interpolation as well as compared to segmentation tools that also consider the underlying image data. Biomedisa can be used for different 3D imaging modalities and various biomedical applications.

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