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Journal article
Hydra image processor: 5-D GPU image analysis library with MATLAB and python wrappers
BIOINFORMATICS, v 35(24), pp 5393-5395
15 Dec 2019
PMID: 31240306
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A Summary: Light microscopes can now capture data in five dimensions at very high frame rates producing terabytes of data per experiment. Five-dimensional data has three spatial dimensions (x, y, z), multiple channels (lambda) and time (t). Current tools are prohibitively time consuming and do not efficiently utilize available hardware. The hydra image processor (HIP) is a new library providing hardware-accelerated image processing accessible from interpreted languages including MATLAB and Python. HIP automatically distributes data/computation across system and video RAM allowing hardware-accelerated processing of arbitrarily large images. HIP also partitions compute tasks optimally across multiple GPUs. HIP includes a new kernel renormalization reducing boundary effects associated with widely used padding approaches.
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Details
- Title
- Hydra image processor: 5-D GPU image analysis library with MATLAB and python wrappers
- Creators
- Eric Wait - Drexel UniversityMark Winter - Drexel UniversityAndrew R. Cohen - Drexel University
- Publication Details
- BIOINFORMATICS, v 35(24), pp 5393-5395
- Publisher
- Oxford Univ Press
- Number of pages
- 3
- Grant note
- R01AG041861 / NIH NIA; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute on Aging (NIA)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000509361200066
- Scopus ID
- 2-s2.0-85077782579
- Other Identifier
- 991019168705604721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Biochemical Research Methods
- Biotechnology & Applied Microbiology
- Computer Science, Interdisciplinary Applications
- Mathematical & Computational Biology
- Statistics & Probability