ArticleBioinformatics (Oxford, England)2019
Hydra image processor: 5-D GPU image analysis library with MATLAB and python wrappers.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- A workflow for quantifying cell quiescence in 3D spheroids.Biochemistry and biophysics reports · 2026Article
- Exploring the Spatial Limits of Extracellular Vesicles-Mediated Intercellular Communication.Journal of extracellular vesicles · 2025Article
- A Kolmogorov metric embedding for live cell microscopy signaling patterns.Bioinformatics advances · 2025Article
- LEVERSC: Cross-Platform Scriptable Multichannel 3-D Visualization for Fluorescence Microscopy Images.Frontiers in bioinformatics · 2022Article
- CALM supports clathrin-coated vesicle completion upon membrane tension increase.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Article
- Calcium-vesicles perform active diffusion in the sea urchin embryo during larval biomineralization.PLoS computational biology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
summaryLight 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 (λ) 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. AVAILABILITY AND IMPLEMENTATION: HIP is free and open source software released under the BSD 3-Clause License. Source code and compiled binary files will be maintained on http://www.hydraimageprocessor.com. A comprehensive description of all MATLAB and Python interfaces and user documents are provided. HIP includes GPU-accelerated support for most common image processing operations in 2-D and 3-D and is easily extensible. HIP uses the NVIDIA CUDA interface to access the GPU. CUDA is well supported on Windows and Linux with macOS support in the future.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.