scholarly journals An Open Source, Fast Ultrasound B-Mode Implementation for Commodity Hardware

2010 ◽  
Author(s):  
Matthew Mccormick
Keyword(s):  
Image Processing ◽  
Fourier Transform ◽  
Open Source ◽  
High Performance ◽  
Phased Array ◽  
Memory Consumption ◽  
Commodity Hardware ◽  
Processing Pipeline ◽  
Scan Conversion ◽  
Rf Signal

This document describes an open source, high performance ultrasound B-Mode implementation based on the Insight Toolkit (ITK). ITK extensions are presented to calculate the radio-frequency (RF) signal envelope. A variety of 1D Fast Fourier Transform options are introduced including VNL, FFTW, and an OpenCL solution. Scan conversion is implemented for phased array or curvilinear transducers. The entire image processing pipeline is streamable to limit memory consumption during multi-frame or 3D acquisitions with the introduction of an itk::StreamingResampleImageFilter.

scholarly journals ZebrafishMiner: an open source software for interactive evaluation of domain-specific fluorescence in zebrafish

2017 ◽  
Vol 3 (2) ◽  
pp. 199-202
Author(s):  
Markus Reischl ◽  
Andreas Bartschat ◽  
Urban Liebel ◽  
Jochen Gehrig ◽  
Ference Müller ◽  
...  
Keyword(s):  
Image Processing ◽  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Drug Effects ◽  
Processing Parameters ◽  
Domain Specific ◽  
Processing Pipeline ◽  
Open Source Software Package ◽  
Programming Knowledge

AbstractHigh-throughput microscopy makes it possible to observe the morphology of zebrafish on large scale to quantify genetic, toxic or drug effects. The image acquisition is done by automated microscopy, images are evaluated automatically by image processing pipelines, tailored specifically to the requirements of the scientific question. The transfer of such algorithms to other projects, however, is complex due to missing guidelines and lack of mathematical or programming knowledge. In this work, we implement an image processing pipeline for automatic fluorescence quantification in user-defined domains of zebrafish embryos and larvae of different age. The pipeline is capable of detecting embryos and larvae in image stacks and quantifying domain activity. To make this protocol available to the community, we developed an open source software package called „ZebrafishMiner“ which guides the user through all steps of the processing pipeline and makes the algorithms available and easy to handle. We implemented all routines in an MATLAB-based graphical user interface (GUI) that gives the user control over all image processing parameters. The software is shipped with a manual of 30 pages and three tutorial datasets, which guide the user through the manual step by step. It can be downloaded at https://sourceforge.net/projects/scixminer/.

scholarly journals Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform

2016 ◽  
Vol 22 (3) ◽  
pp. 238-249 ◽  
Author(s):  
Ioannis K. Moutsatsos ◽  
Imtiaz Hossain ◽  
Claudia Agarinis ◽  
Fred Harbinski ◽  
Yann Abraham ◽  
...  
Keyword(s):  
Image Processing ◽  
Open Source ◽  
High Throughput Screening ◽  
High Performance ◽  
Heterogeneous Data ◽  
Scientific Data ◽  
Source Image ◽  
Integration System ◽  
Continuous Integration ◽  
Processing Platform

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an “off-the-shelf,” open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

scholarly journals A new implementation of itk::ImageToImageFilter for efficient parallelization of image processing algorithms using Intel Threading Building Blocks

2016 ◽  
Author(s):  
Amir Jaberzadeh ◽  
Benoit Scherrer ◽  
Simon Warfield
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Medical Imaging ◽  
Open Source ◽  
High Performance ◽  
Job Scheduling ◽  
Building Blocks ◽  
Reconstruction Image ◽  
Imaging Algorithms ◽  
Very High

Modern medical imaging makes use of high performance computing to accelerate image acquisition, image reconstruction, image visualization and image analysis. Software libraries that provide implementations of key medical imaging algorithms need to efficiently exploit modern CPU architectures. In particular, workstations with small numbers of cores are being replaced by very high core count architectures, and by many integrated core architectures, which offer acceleration by vectorization and multi-threading.The Insight Toolkit (ITK) is the premier open source implementation of medical imaging algorithms, with a generic design for image processing filters that allows for many developers to rapidly incorporate these algorithms in to new applications. While ITK filters benefit from a generic, platform independent multithreading capability, the current implementation is difficult to exploit to achieve very high performance. Specifically, ITK relies on a static decomposition of the image into subsets of equal size which can be highly inefficient. Threads that terminate early due to uneven work throughout the image finish early and do not contribute further to the processing of more complex regions, leading to idle computational resources and longer execution times. Performance is also difficult to coordinate across multiple algorithms, as the ITK filter assumes each filter operates independently but the global implementation has an impact across filters.In this work, we propose a novel, simple to use, high performance multithreading capability for ITK that accelerates the itk::ImageToImageFilter. We utilise a workpile data decomposition strategy, and leave the task of optimal job scheduling on CPU cores to the library called Threading Building Blocks (TBB). We demonstrate the efficacy of multi-threading with TBB in comparison to the itk::Multithreader class, through three simple example image analysis algorithms.Our implementation provides a new multi-threaded itk::ImageToImageFilter that can be conveniently reused to provide simple and efficient multi-threaded code across applications and algorithm libraries. Our new implementation is distributed as open-source software to the community and is straightforward to adopt.

Matlab and Parallel Computing

2012 ◽  
Vol 17 (4) ◽  
pp. 207-216 ◽  
Author(s):  
Magdalena Szymczyk ◽  
Piotr Szymczyk
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Parallel Computing ◽  
Distributed Computing ◽  
Control Systems ◽  
High Performance ◽  
Parallel Applications ◽  
Process Simulations ◽  
Key Features ◽  
Financial Process

Abstract The MATLAB is a technical computing language used in a variety of fields, such as control systems, image and signal processing, visualization, financial process simulations in an easy-to-use environment. MATLAB offers "toolboxes" which are specialized libraries for variety scientific domains, and a simplified interface to high-performance libraries (LAPACK, BLAS, FFTW too). Now MATLAB is enriched by the possibility of parallel computing with the Parallel Computing ToolboxTM and MATLAB Distributed Computing ServerTM. In this article we present some of the key features of MATLAB parallel applications focused on using GPU processors for image processing.

A High Performance Image Processing Unit for On-orbit Servicing

2006 ◽  
Author(s):  
Hiroshi Yamamoto ◽  
Yasufumi Nagai ◽  
Shinichi Kimura ◽  
Hiroshi Takahashi ◽  
Satoko Mizumoto ◽  
...  
Keyword(s):  
Image Processing ◽  
High Performance ◽  
Processing Unit

The Utilization of Ftir (Fourier Transform Infra-Red) Method Combined with Chemometrics For Authentication of Indonesian Coffee Powder

2017 ◽  
Vol 9 (3) ◽  
Author(s):  
Firmansyah A. ◽  
Winingsih W. ◽  
Soebara Y S
Keyword(s):  
Fourier Transform ◽  
Natural Product ◽  
High Performance ◽  
Principal Component ◽  
Raw Material ◽  
Attenuated Total Reflectance ◽  
Coffee Bean ◽  
Product Analysis ◽  
Total Reflectance ◽  
And Cluster Analysis

Analysis of natural product remain challenging issues for analytical chemist, since natural products are complicated system of mixture. The most popular methods of choice used for quality control of raw material and finished product are high performance liquid chromatography (HPLC), gas chromatography (GC) and mass spectrometry (MS). The utilization of FTIR-ATR (Fourier Transform Infrared-Attenuated Total Reflectance) method in natural product analysis is still limited. This study attempts to expand the use of FTIR spectroscopy in authenticating Indonesian coffee powder.The coffee samples studied were taken from nine regions in Indonesia, namely Aceh Gayo, Flores, Kintamani, Mandheling, Papua, Sidikalang, Toraja, Kerinci and Lampung.The samples in the form of coffee bean from various regions were powdered . The next step conducted was to determine the spectrum using the FTIR-ATR (Attenuated Total Reflectance) using ZnSe crystal of 8000 resolution. Spectrum samples, then, were analyzed using chemometrics. The utilized chemometric model was the principal component analysis (PCA) and cluster analysis (CA). Based on the chemometric analysis, there are similarities between Aceh Gayo coffee with Toraja coffee, Mandailing coffee, Kintamani coffee and Flores coffee. Sidikalang coffee has a similarity to Flores coffee; Papua coffee has a similarity to Sidikalang coffee; Lampung coffee has a similarity to Sidikalang coffee, while Kerinci coffee has a similarity to Papua coffee.

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