Hehe, the first game of life I code (in #FijiSc
using #BigDataViewer
obviously). Naive implementation, but still functionally defined and lazy computed - see how the data arrives as I scroll, and is cached.
A tradition - showing off with #BigDataViewer This time by making the ABBA (go.epfl.ch/abba) logo with 4900 multiresolution images, each with a custom affine transform. Smooth when zoomed in, lagging a bit from afar but still very manageable.
A classic in dynamical systems: the Lorenz attractor, computed and visualized using #Fiji in #BigDataViewer
Too lazy for a movie today, but look at this nice procedural image! It's a plane wave spherically transformed 2 times. Still with #BigDataViewer

Spherical coordinates live transformation with #BigDataViewer .

Left: a view of a drosophila egg chamber, with a fitted ellipsoid on top of it,

right: a theta / phi view of the egg chamber. I also scroll along the r dimension, and rotate the poles.

Another day, another #BigDataViewer
video. This time an orthoviewer + a BigVolumeViewer. Dataset = Allen Brain Atlas CCFv3.

All those demos will be accessible in Fiji with the PTBIOP update site soon.
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

Why would one want to run machine learning inference from #java?

To do so on 3D, 4D, ND datasets, trivially accessible from image processing and visualization libraries such as #ImgLib2, the #BigDataViewer, #LabKit and more, all integral parts of #FijiSc.

* LabKit: https://imagej.net/plugins/labkit/

* BigDataViewer: https://imagej.net/plugins/bdv/

* ImgLib2: https://imagej.net/libs/imglib2/

* Fiji: https://fiji.sc

Labkit - Intuitive Pixel Classification in Fiji

The ImageJ wiki is a community-edited knowledge base on topics relating to ImageJ, a public domain program for processing and analyzing scientific images, and its ecosystem of derivatives and variants, including ImageJ2, Fiji, and others.

ImageJ Wiki
BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples - Nature Methods

BigStitcher enables fast and accurate alignment and reconstruction of terabyte-sized imaging datasets of cleared and expanded samples.

Nature

#FIJI development is mainly concentrated at #LOCI based at #UWMadison.

#imglib2 development is currently focused at @HHMI Janelia where I work.

Tobias Pietzsch, an independent developer, is now picking up of #imglib2 and #BigDataViewer development with support from #CZI and @HHMI .