![]() ![]() We also give an insight into quality assurance methods, which help to ensure good scientific practice when modernizing BIA workflows and refactoring code.Ĭell membranes create functional compartments and maintain diverse content and activities. Accordingly, we show how to measure workflow performance. In terms of image processing, refactoring means restructuring an existing macro without changing measurement results, but rather improving processing speed. These commands are then assembled to refactor the pre-existing workflow. We then introduce ways to discover CLIJ commands as counterparts of classic ImageJ methods. ![]() To demonstrate the procedure, we translate a formerly published BIA workflow for examining signal intensity changes at the nuclear envelope, caused by cytoplasmic redistribution of a fluorescent protein (Miura, 2020). Our suggested approach neither requires a profound expertise in high performance computing, nor to learn a new programming language such as OpenCL. We present a guide for transforming state-of-the-art image processing workflows into GPU-accelerated workflows using the ImageJ Macro language. , 2020), enables biologists and bioimage analysts to speed up time-consuming analysis tasks by adding support for the Open Computing Language (OpenCL) for programming GPUs (Khronos-Group, 2020) in ImageJ. ![]() As an alternative to established acceleration techniques, such as ImageJ’s batch mode, we explore how GPUs can be exploited to accelerate classic image processing. Even though general machine learning and convolutional neural networks are not new approaches to image processing, their importance for life science is increasing.Īs their application is now at hand due to the rise of advanced computing hardware, namely graphics processing units (GPUs), a natural question is if GPUs can also be exploited for classic image processing in ImageJ (Schneider et al. Nowadays, image data scientists join forces with artificial intelligence researchers, incorporating more and more machine learning algorithms into BIA workflows. Feel free to ask me any questions either here or email/PM if something is not clear.Modern life science increasingly relies on microscopic imaging followed by quantitative bioimage analysis (BIA). It might be worth getting in touch with the Olympus software developers too? However, I would still appreciate it if you could try to find a workaround either via the Fiji plug-in or the command line tools (thinking mostly bfconvert) allowing me to convert from. index.htmlĪs a general note, I realize that the problem probably lies mostly within Olympus and their software engineers for not thinking about this problem when designing the. ![]() > The command line tools were downloaded from here. The smaller images are X:Y - 2048:2048 pixels, pixel type: uint16, have 5-8 z slices, no time series. The size of the images vary as they are made by stitching a variable number of smaller images. > All my images are collected on the Olympus FV 3000 using the FluoView software with air objective x20. > The Bio-formats plug-in on both of them is Release 5.8.2 Build date: > On both of them I am running Fiji (ImageJ) version 1.52d and Java 1.8.0_172 (64-bit) > The issue has been reproduced on both Linux Ubuntu 16.04 LTS and macOS High Sierra version 10.13.5 What happens is that when I run the bfconvert it just gets stuck and doesn't output anything with the large stitched files. Analogously to the Fiji plug-in that worked for files which are stitched AND 1GB and NOT stitched but not for stitched AND >1GB. The Bio-formats Fiji plug-in works fine for files which are stitched AND 1GB and NOT stitched but not for stitched AND >1GB.Īnother thing that I have tried is using the Bio-formats Command line tools, specifically the function bfconvert to convert the. When you are imaging a large object (in my case a fluorescent brain slice) you can choose an option to take many images that tile the entire object and then stitch them together into a single image. I have acquired this file using an Olympus microscope FV 3000. When I try to open it, FIji says "Reading file header" but it never finishes reading and opening the file. oir file is large (>1GB) and consisting of stitched images it won't open via the Bio-formats FIji plug-in. I have the following problem with Olympus. Would it be also useful to upload a smaller file that works as a "positive control"? I have uploaded an example file using this link: and the file is called: Example_image_1.oir. This topic is similar to another one ( viewtopic.php?f=13&t=8362&p=18787&hilit=martin#p18787) however my problem is slightly different so this is not a duplication. My name is Alex, currently PhD student in the University of Oxford. ![]()
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