#imagej — Public Fediverse posts

Light-Sheet Image Analysis Workshop 2026

The Light-Sheet Image Analysis Workshop is a five-day intensive course that will take place in Santiago, Chile, from January 5–9, 2026, designed for students and researchers who wish to gain foundational skills in the processing and analysis of light-sheet microscopy imaging data.

The application deadline has been extended until August 8, 2025! The workshop is free to attend and travel fellowships are available. Learn more and apply here:

https://lightsheetchile.cl/light-sheet-image-analysis-workshop-2026-2/

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URL: https://brunovellutini.com/posts/light-sheet-image-analysis-workshop-2026/

#event #imageProcessing #imagej #lightsheet #microscopy

Yep, it lags a little. But still quite impressive considering that each "pixel" is a 150 MPixel multires image. Overall the total number of 'adressable' pixels in this 2D image are 225x225x150 Mpix = 7.6 Tera pixels. #ImageJ
#Fiji
#BigDataViewer

Yep, it lags a little. But still quite impressive considering that each "pixel" is a 150 MPixel multires image. Overall the total number of 'adressable' pixels in this 2D image are 225x225x150 Mpix = 7.6 Tera pixels. #ImageJ
#Fiji
#BigDataViewer

Yep, it lags a little. But still quite impressive considering that each "pixel" is a 150 MPixel multires image. Overall the total number of 'adressable' pixels in this 2D image are 225x225x150 Mpix = 7.6 Tera pixels. #ImageJ
#Fiji
#BigDataViewer

I am honestly floored at the #SegmentAnything implementation for #ImageJ / #Fiji

Even running on a laptop, once loaded, it's incredibly quick.

Moreover, it's a super-simple install which is a major barrier to many #AI #DeepLearning implementations.

Time to play around with some #Microscopy and #DigitalPathology data!

Details here: https://github.com/segment-anything-models-java/SAMJ-IJ
Photo source: https://www.pexels.com/photo/photo-of-railway-on-mountain-near-houses-1658967/

From Oliver Burri via #ImageJ mailing list:

SwitZerland’s Image and Data Analysis School #ZIDAS2024

At ETH Zurich from June 23th (Yes, Sunday!) to June 28th 2024.

Are you a life scientist working with microscopy images?
Do you feel like you could use a nudge in the right direction in order to dive into quantitative image analysis ?
Want to learn to program in ImageJ macro language, use novel deep learning tools, discover best practices in image processing all while working on your own data?

The program will focus on hands-on work using the best open source tools available to the BioImage Analysis community.

Registration is open until 2024-03-16.

https://2024.zidas.org
#BioimageInformatics #ImageProcessing

From Oliver Burri via #ImageJ mailing list:

SwitZerland’s Image and Data Analysis School #ZIDAS2024

At ETH Zurich from June 23th (Yes, Sunday!) to June 28th 2024.

Are you a life scientist working with microscopy images?
Do you feel like you could use a nudge in the right direction in order to dive into quantitative image analysis ?
Want to learn to program in ImageJ macro language, use novel deep learning tools, discover best practices in image processing all while working on your own data?

The program will focus on hands-on work using the best open source tools available to the BioImage Analysis community.

Registration is open until 2024-03-16.

https://2024.zidas.org
#BioimageInformatics #ImageProcessing

From Oliver Burri via #ImageJ mailing list:

SwitZerland’s Image and Data Analysis School #ZIDAS2024

At ETH Zurich from June 23th (Yes, Sunday!) to June 28th 2024.

Are you a life scientist working with microscopy images?
Do you feel like you could use a nudge in the right direction in order to dive into quantitative image analysis ?
Want to learn to program in ImageJ macro language, use novel deep learning tools, discover best practices in image processing all while working on your own data?

The program will focus on hands-on work using the best open source tools available to the BioImage Analysis community.

Registration is open until 2024-03-16.

https://2024.zidas.org
#BioimageInformatics #ImageProcessing

@blog I write about biology, imaging, coding, music, and other things I find interesting to share.

Here are some keywords from the latest posts:

#Science #Biology #Outreach #Cifonauta #MarineInvertebrates #Flies #EvoDevo #DevBio #Wnt #Embryo #Larva #ImageJ #ImageProcessing #SciArt

Have you discovered the image processing forum yet? https://forum.image.sc

Featuring tutorials, requests for guidance, help, discussion of new features and documentation for open source software #FijiSc #ImageJ #CellProfiler #DeepLabCut #Icy #ilastik #napari #QuPath #scikitimage #StarDist and many more.

#java #python #kotlin #groovy

Have you discovered the image processing forum yet? https://forum.image.sc

Featuring tutorials, requests for guidance, help, discussion of new features and documentation for open source software #FijiSc #ImageJ #CellProfiler #DeepLabCut #Icy #ilastik #napari #QuPath #scikitimage #StarDist and many more.
#java #python #kotlin #groovy

Now onto #FijiSc: Fiji is a recursive acronym meaning "Fiji is just ImageJ" https://fji.sc (and the paper https://www.nature.com/articles/nmeth.2019 ) –and #ImageJ is a #java open source software for image processing https://imagej.nih.gov/ij/index.html written by Wayne Rasband from the #NIH Research Branch.

An analogy: think of ImageJ as the kernel and Fiji as the rest of the operating system.

#FijiSc brings to #ImageJ:
(1) a package manager to install and update plugins, and that crucially enables reproducible science by exporting the whole set of plugins and libraries as an executable;
(2) a Script Editor https://imagej.net/scripting/script-editor supporting many languages (#python, #groovy #ruby #scala #clojure and more), all with access to a huge collection of #JVM libraries;
(3) huge amount of libraries such as #ImgLib2, #JFreeChart for plotting, for GUIs, etc.

There are many, many plugins. A tiny sample:

Machine learning-based image segmentation:
- #LabKit https://imagej.net/plugins/labkit/
- #WEKA Trainable Segmentation https://imagej.net/plugins/tws/index

3D/4D/ND Visualization:
- 3D/4D Viewer #3DViewer https://imagej.net/plugins/3d-viewer/index with ray-tracing, orthoslices, volume rendering, and more
- #BigDataViewer #BDV https://imagej.net/plugins/bdv/index for interactively navigate N-dimensional image volumes larger than RAM

Image registration and serial section alignment:
- #BigStitcher for registering 3D/4D tiled datasets, with multiview deconvolution and more https://imagej.net/plugins/bigstitcher/index
- #TrakEM2 for montaging in 2D and alinging in 3D collections of serial sections, typically from #vEM (volume electron microscopy) https://syn.mrc-lmb.cam.ac.uk/acardona/INI-2008-2011/trakem2.html
- #mpicbg libraries for extracting #SIFT and #MOPS features, then finding feature correspondences and estimating rigid and elastic transformation models https://www.nature.com/articles/nmeth.2072

Summarizing #FijiSc is impossible. See the online forum where questions find answers by the hand of the broader community of users and developers https://forum.image.sc/

Now onto #FijiSc: Fiji is a recursive acronym meaning "Fiji is just ImageJ" https://fji.sc (and the paper https://www.nature.com/articles/nmeth.2019 ) –and #ImageJ is a #java open source software for image processing https://imagej.nih.gov/ij/index.html written by Wayne Rasband from the #NIH Research Branch.

An analogy: think of ImageJ as the kernel and Fiji as the rest of the operating system.

#FijiSc brings to #ImageJ:
(1) a package manager to install and update plugins, and that crucially enables reproducible science by exporting the whole set of plugins and libraries as an executable;
(2) a Script Editor https://imagej.net/scripting/script-editor supporting many languages (#python, #groovy #ruby #scala #clojure and more), all with access to a huge collection of #JVM libraries;
(3) huge amount of libraries such as #ImgLib2, #JFreeChart for plotting, for GUIs, etc.

There are many, many plugins. A tiny sample:

Machine learning-based image segmentation:
- #LabKit https://imagej.net/plugins/labkit/
- #WEKA Trainable Segmentation https://imagej.net/plugins/tws/index

3D/4D/ND Visualization:
- 3D/4D Viewer #3DViewer https://imagej.net/plugins/3d-viewer/index with ray-tracing, orthoslices, volume rendering, and more
- #BigDataViewer #BDV https://imagej.net/plugins/bdv/index for interactively navigate N-dimensional image volumes larger than RAM

Image registration and serial section alignment:
- #BigStitcher for registering 3D/4D tiled datasets, with multiview deconvolution and more https://imagej.net/plugins/bigstitcher/index
- #TrakEM2 for montaging in 2D and alinging in 3D collections of serial sections, typically from #vEM (volume electron microscopy) https://syn.mrc-lmb.cam.ac.uk/acardona/INI-2008-2011/trakem2.html
- #mpicbg libraries for extracting #SIFT and #MOPS features, then finding feature correspondences and estimating rigid and elastic transformation models https://www.nature.com/articles/nmeth.2072

Summarizing #FijiSc is impossible. See the online forum where questions find answers by the hand of the broader community of users and developers https://forum.image.sc/

Now onto #FijiSc: Fiji is a recursive acronym meaning "Fiji is just ImageJ" https://fji.sc (and the paper https://www.nature.com/articles/nmeth.2019 ) –and #ImageJ is a #java open source software for image processing https://imagej.nih.gov/ij/index.html written by Wayne Rasband from the #NIH Research Branch.

An analogy: think of ImageJ as the kernel and Fiji as the rest of the operating system.

#FijiSc brings to #ImageJ:
(1) a package manager to install and update plugins, and that crucially enables reproducible science by exporting the whole set of plugins and libraries as an executable;
(2) a Script Editor https://imagej.net/scripting/script-editor supporting many languages (#python, #groovy #ruby #scala #clojure and more), all with access to a huge collection of #JVM libraries;
(3) huge amount of libraries such as #ImgLib2, #JFreeChart for plotting, for GUIs, etc.

There are many, many plugins. A tiny sample:

Machine learning-based image segmentation:
- #LabKit https://imagej.net/plugins/labkit/
- #WEKA Trainable Segmentation https://imagej.net/plugins/tws/index

3D/4D/ND Visualization:
- 3D/4D Viewer #3DViewer https://imagej.net/plugins/3d-viewer/index with ray-tracing, orthoslices, volume rendering, and more
- #BigDataViewer #BDV https://imagej.net/plugins/bdv/index for interactively navigate N-dimensional image volumes larger than RAM

Image registration and serial section alignment:
- #BigStitcher for registering 3D/4D tiled datasets, with multiview deconvolution and more https://imagej.net/plugins/bigstitcher/index
- #TrakEM2 for montaging in 2D and alinging in 3D collections of serial sections, typically from #vEM (volume electron microscopy) https://syn.mrc-lmb.cam.ac.uk/acardona/INI-2008-2011/trakem2.html
- #mpicbg libraries for extracting #SIFT and #MOPS features, then finding feature correspondences and estimating rigid and elastic transformation models https://www.nature.com/articles/nmeth.2072

Summarizing #FijiSc is impossible. See the online forum where questions find answers by the hand of the broader community of users and developers https://forum.image.sc/

Now onto #FijiSc: Fiji is a recursive acronym meaning "Fiji is just ImageJ" https://fji.sc (and the paper https://www.nature.com/articles/nmeth.2019 ) –and #ImageJ is a #java open source software for image processing https://imagej.nih.gov/ij/index.html written by Wayne Rasband from the #NIH Research Branch.

An analogy: think of ImageJ as the kernel and Fiji as the rest of the operating system.

#FijiSc brings to #ImageJ:
(1) a package manager to install and update plugins, and that crucially enables reproducible science by exporting the whole set of plugins and libraries as an executable;
(2) a Script Editor https://imagej.net/scripting/script-editor supporting many languages (#python, #groovy #ruby #scala #clojure and more), all with access to a huge collection of #JVM libraries;
(3) huge amount of libraries such as #ImgLib2, #JFreeChart for plotting, for GUIs, etc.

There are many, many plugins. A tiny sample:

Machine learning-based image segmentation:
- #LabKit https://imagej.net/plugins/labkit/
- #WEKA Trainable Segmentation https://imagej.net/plugins/tws/index

3D/4D/ND Visualization:
- 3D/4D Viewer #3DViewer https://imagej.net/plugins/3d-viewer/index with ray-tracing, orthoslices, volume rendering, and more
- #BigDataViewer #BDV https://imagej.net/plugins/bdv/index for interactively navigate N-dimensional image volumes larger than RAM

Image registration and serial section alignment:
- #BigStitcher for registering 3D/4D tiled datasets, with multiview deconvolution and more https://imagej.net/plugins/bigstitcher/index
- #TrakEM2 for montaging in 2D and alinging in 3D collections of serial sections, typically from #vEM (volume electron microscopy) https://syn.mrc-lmb.cam.ac.uk/acardona/INI-2008-2011/trakem2.html
- #mpicbg libraries for extracting #SIFT and #MOPS features, then finding feature correspondences and estimating rigid and elastic transformation models https://www.nature.com/articles/nmeth.2072

Summarizing #FijiSc is impossible. See the online forum where questions find answers by the hand of the broader community of users and developers https://forum.image.sc/

Above, my #introduction of interests. Here, who I am, what I do: a neuroscientist at the #MRCLMB and University of Cambridge, UK, studying the neural circuit basis of behavior, originally in #Drosophila but now also in #cephalopods (#pygmysquid #Idiosepius), the lancelet #Amphioxus and other animals. Our main approach: whole brain #connectomics with #vEM (volume electron microscopy) as the basis for computational modeling to guide neuronal activity perturbation and monitoring experiments with #optogenetics and #electrophysiology (#ephys for short).
Once upon a time I founded the #ImageJ -based #TrakEM2 software for image registration and neuronal arbor reconstruction and annotation, which spurred founding the #FijiSc (https://fiji.sc) image processing software, and later the #CATMAID web-based software for #connectomics.
Always open to inquires from prospective students and postdocs, and collaborations.