OpenMV is an open source machine vision system. It’s designed to be easy-to-use, with a gentle learning curve. They want this to be the “Arduino of Machine Vision”. The software IDE is free and open. The hardware is available from Sparkfun and other places. Color blob detection, eye and pupil tracking, motion detection, etc. You
Moiré lenses are cool: two patterned diffractive optical elements are rotated relative to each other to vary the power of the “lens”. Just watch the video (below). Demonstration of focus-tunable diffractive Moiré-lenses Stefan Bernet, Walter Harm, and Monika Ritsch-Marte Vol. 21, Issue 6, pp. 6955-6966 (2013) •https://doi.org/10.1364/OE.21.006955 And their 2008 theoretical work.
Pixy is an open source computer vision system. Mostafa Nashaat, Robert Sachdev, and colleagues including Matthew Larkum have developed software for use with the Pixy, that can be used to track mouse behavior, including free movement around an enclosure (top image), or track the movement of individual whiskers (bottom image), all at 50 Hz. Here’s
We recently tweeted about a preprint from Eftychios A Pnevmatikakis and Andrea Giovannucci (code). The preprint is on motion correction for calcium imaging data. It is a nice quick read and discusses earlier work in the area. (That’s Eftychios of constrained-non-negative-matrix-factorization-for-calcium-imaging-analysis fame). Marius Pachitariu recognized the algorithm as very similar to one that he uses
Max Planck Florida is running their imaging course again and there’s still time to apply. They’ve got great faculty including Na Ji, Ryohei Yasuda, Yi Zuo, Chris Xu, Jeff Lichtman, Naomi Kamasawa, and more!
The Allen Institute has released the first set of data from their Brain Observatory project. Many of you already know about this, but I wanted to post about it to encourage people to take a bit of time to check out the data set themselves. They have a github page with materials that can help
Andrew Lim wrote in to discuss strategies on dealing with ripple noise in 2-photon imaging systems, particularly when using resonant scanners. He writes: This isn’t so much a tip as a problem with resonant two-photon scopes that several people have told me they also have but I haven’t seen a solution for (other people apparently
A world-class in vivo patch clamp electrophysiologist, Ian Duguid, is recruiting to his lab. Ian provides excellent training, and his lab is in a tremendous setting: Edinburgh. Ian’s also one of the current leaders of the famous CSHL Ion Channels course. By the way, his web site also has some interesting machine drawings and other
Peter Weir has a nice write up and directions on how to make the fly holder from his recent paper. He has some other useful notes that are worth checking out too: github, blog, web page. Hat tip to John Tuthill (link)
Results are similar to the slow version of TurboReg, but it runs about twice as fast as the fast version of TurboReg. Here’s the paper. Here’s the code.
Peng Xi (Peking University) shared this resource his lab has developed: software for processing images for structured illumination (a superresolution technique). Here’s the Github repository. And here’s the paper (pay wall). Previously on Labrigger… Structured illumination Notes from an email exchange with the late Mats Gustafsson, a pioneer of structured illumination microscopy
I tweeted about this last fall. This is the best algorithm I’ve seen for segmenting and extracting time course from calcium imaging data. Eftychios Pnevmatikakis developed the code in Liam Paninski’s lab. The work is reported in a pair of papers in Neuron, and the code is freely available (links below). The source separation works
Collaborative Approach for eNhanced Denoising under Low-light Excitation, or CANDLE, is a denoising algorithm specialized for the type of images that are acquired in 2-photon imaging applications. There’s code for both ImageJ and MATLAB available at that link. Here’s a write up on it. The raw images are on the left, and the denoised (via
Microscopists are often adapting techniques pioneered for astronomy. Adaptive optics is the example you all probably know. Relatedly, phase retrieval was originally developed for telescopic imaging systems, and was adapted for high NA microscopic imaging systems by Mats Gustafsson and colleagues (Hanser et al. 2003 Optics Letters). A couple of excellent optics people, Kyle Douglass
“> Leonardo Lupori and Raffaele Mazziotti are two fellows in lab of the excellent Tommaso Pizzorusso. They have developed an intrinsic signal optical imaging rig and are sharing all of the materials. Here’s their web site with the resources and links. More on intrinsic imaging… Yet more again…
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