Instant Feedback Rapid Prototyping for GPU-Accelerated Computation, Manipulation, and Visualization of Multidimensional Data

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Objective: We have created an open-source application and framework for rapid GPU-accelerated prototyping, targeting image analysis, including volumetric images such as CT or MRI data.

Methods: A visual graph editor enables the design of processing pipelines without programming. Run-time compiled compute shaders enable prototyping of complex operations in a matter of minutes.

Results: GPU-acceleration increases processing the speed by at least an order of magnitude when compared to traditional multithreaded CPU-based implementations, while offering the flexibility of scripted implementations.

Conclusion: Our framework enables real-time, intuition-guided accelerated algorithm and method development, supported by built-in scriptable visualization.

Significance: This is, to our knowledge, the first tool for medical data analysis that provides both high performance and rapid prototyping. As such, it has the potential to act as a force multiplier for further research, enabling handling of high-resolution datasets while providing quasi-instant feedback and visualization of results.

LanguageEnglish
Article number2046269
Number of pages9
JournalInternational journal of biomedical imaging
Volume2018
DOIs
StatusPublished - 2018

Fingerprint

Rapid prototyping
Visualization
Feedback
Intuition
Processing
Magnetic resonance imaging
Image analysis
Program processors
Pipelines
Research
Graphics processing unit
Datasets

Keywords

  • Journal Article

ASJC Scopus subject areas

  • Biotechnology
  • Molecular Biology
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)

Fields of Expertise

  • Human- & Biotechnology
  • Information, Communication & Computing

Treatment code (Nähere Zuordnung)

  • Application

Cite this

@article{70fca573a2ba415ab3073cdb5462988f,
title = "Instant Feedback Rapid Prototyping for GPU-Accelerated Computation, Manipulation, and Visualization of Multidimensional Data",
abstract = "Objective: We have created an open-source application and framework for rapid GPU-accelerated prototyping, targeting image analysis, including volumetric images such as CT or MRI data.Methods: A visual graph editor enables the design of processing pipelines without programming. Run-time compiled compute shaders enable prototyping of complex operations in a matter of minutes.Results: GPU-acceleration increases processing the speed by at least an order of magnitude when compared to traditional multithreaded CPU-based implementations, while offering the flexibility of scripted implementations.Conclusion: Our framework enables real-time, intuition-guided accelerated algorithm and method development, supported by built-in scriptable visualization.Significance: This is, to our knowledge, the first tool for medical data analysis that provides both high performance and rapid prototyping. As such, it has the potential to act as a force multiplier for further research, enabling handling of high-resolution datasets while providing quasi-instant feedback and visualization of results.",
keywords = "Journal Article, Genomics, bioinformatics",
author = "Maximilian Malek and Sensen, {Christoph W}",
year = "2018",
doi = "10.1155/2018/2046269",
language = "English",
volume = "2018",
journal = "International journal of biomedical imaging",
issn = "1687-4188",
publisher = "Hindawi Publishing Corporation",

}

TY - JOUR

T1 - Instant Feedback Rapid Prototyping for GPU-Accelerated Computation, Manipulation, and Visualization of Multidimensional Data

AU - Malek,Maximilian

AU - Sensen,Christoph W

PY - 2018

Y1 - 2018

N2 - Objective: We have created an open-source application and framework for rapid GPU-accelerated prototyping, targeting image analysis, including volumetric images such as CT or MRI data.Methods: A visual graph editor enables the design of processing pipelines without programming. Run-time compiled compute shaders enable prototyping of complex operations in a matter of minutes.Results: GPU-acceleration increases processing the speed by at least an order of magnitude when compared to traditional multithreaded CPU-based implementations, while offering the flexibility of scripted implementations.Conclusion: Our framework enables real-time, intuition-guided accelerated algorithm and method development, supported by built-in scriptable visualization.Significance: This is, to our knowledge, the first tool for medical data analysis that provides both high performance and rapid prototyping. As such, it has the potential to act as a force multiplier for further research, enabling handling of high-resolution datasets while providing quasi-instant feedback and visualization of results.

AB - Objective: We have created an open-source application and framework for rapid GPU-accelerated prototyping, targeting image analysis, including volumetric images such as CT or MRI data.Methods: A visual graph editor enables the design of processing pipelines without programming. Run-time compiled compute shaders enable prototyping of complex operations in a matter of minutes.Results: GPU-acceleration increases processing the speed by at least an order of magnitude when compared to traditional multithreaded CPU-based implementations, while offering the flexibility of scripted implementations.Conclusion: Our framework enables real-time, intuition-guided accelerated algorithm and method development, supported by built-in scriptable visualization.Significance: This is, to our knowledge, the first tool for medical data analysis that provides both high performance and rapid prototyping. As such, it has the potential to act as a force multiplier for further research, enabling handling of high-resolution datasets while providing quasi-instant feedback and visualization of results.

KW - Journal Article

KW - Genomics

KW - bioinformatics

U2 - 10.1155/2018/2046269

DO - 10.1155/2018/2046269

M3 - Article

VL - 2018

JO - International journal of biomedical imaging

T2 - International journal of biomedical imaging

JF - International journal of biomedical imaging

SN - 1687-4188

M1 - 2046269

ER -