TEND(1)
π tend β diffusion image processing and analysis π
okay so bestie, this is tend from the User Commands shelf of the manual. let's get into it π«Ά
β¨ NAME β¨
tend β diffusion image processing and analysis. that's the whole vibe. π
β¨ SYNOPSIS β¨
tend COMMAND [OPTION]...
πΈ DESCRIPTION πΈ
tend(1) is a command-line interface to a lot of the stuff inside βtenβ, which is a C library for diffusion image processing. and ten? it's one library in the βTeemβ collection of libraries. more tea about Teem lives at http://teem.sf.net. and if you want to check out the Teem source yourself, here's literally the command:
svn co https://svn.code.sf.net/p/teem/code/teem/trunk teem
now, real talk for a sec π₯Ί β the long-term maintenance of this software depends on funding, and funding depends on being able to document who is using it and for what. so if tend(1) or Ten has helped your research β and yes, that absolutely includes simple one-off experiments and mundane data hacking, no gatekeeping here β the Teem developers would love to know. there are multiple ways to communicate this:
- in your publications, consider adding a line like this in the Acknowledgments:
Data processing performed with the tend tool, part of the Teem
toolkit available at http://teem.sf.net.
- alternatively, please email glk@uchicago.edu and briefly describe how Teem software has helped in your work.
- also please consider joining the teem-users mailing list β it's the primary forum for feedback, questions, and feature requests. π
and okay, one more thing: just like unu(1), that other Teem command-line binary, it is often useful to chain together invocations of tend(1) with pipes. here's the iconic example, which estimates tensors from DWIs, takes a slice of the tensor volume, computes the standard RGB colormap of the principal eigenvector, and then quantizes it to an 8-bit PNG:
tend estim -i dwi.nhdr -B kvp -knownB0 true \
| tend slice -a 2 -p 30 \
| tend evecrgb -c 0 -a cl2 -gam 1.2 \
| unu quantize -b 8 -min 0 -max 1 -o z30-rgb.png
the way that pipe chain just works? obsessed. πβ¨
π OPTIONS π
(no standalone options live here, bestie β the real menu is the commands below. keep scrolling π)
π COMMANDS π
each of the following has a corresponding man page of its own: for example, tend-about(1) for βtend aboutβ. iykyk π¦
tend about
information about this program and its use β the lil "hi bestie, here's who i am and how to use me" moment. π
tend grads
calculate balanced gradient directions for DWI acquisition. π§
tend epireg
register diffusion-weighted echo-planar images.
tend bmat
calculate B-matrix given gradient directions.
tend estim
estimate tensors from a set of DW images. the main character of the pipeline, fr fr. π
tend sim
simulate DW images from a tensor field.
tend mfit
estimate models from a set of DW images.
tend mconv
convert from one model to another.
tend msim
simulate DW images from an image of models.
tend make
create DT volume from confidence and eigensystem.
tend avg
average across tensor volumes.
tend helix
generate twisting helical tensor field. it's giving spiral core πͺοΈβ¨
tend sten
calculate structure tensors from a scalar field.
tend glyph
generate postscript or ray-traced renderings of 3D glyphs. so pretty it hurts. π¨
tend ellipse
generate postscript renderings of 2D glyphs.
tend anplot
graph anisotropy metric in barycentric coords. π
tend anvol
apply an anisotropy metric to a DT volume.
tend anscale
scale the anisotropic component of the tensors.
tend anhist
generate barycentric histograms of anisotropy.
tend triple
compute volume of shape triples.
tend tconv
convert between different shape triples.
tend point
describe everything about one sample in a DT volume. yes, everything. π
tend slice
slice 3D tensors to get slab/image of 3D/2D tensors. πͺ
tend norm
normalize tensor size.
tend fiber
fiber tractography, from one or more seeds. following the vibes literally. π§΅
tend eval
calculate one or more eigenvalues in a DT volume.
tend evalpow
modify shape by raising eigenvalues to some power.
tend evalclamp
modify shape by clamping eigenvalues in some range.
tend evaladd
modify shape by adding a constant to all eigenvalues.
tend evalmult
modify shape by multiplying eigenvalues by a constant.
tend log
calculates logarithm of the tensor.
tend exp
calculates exp() of the tensor.
tend evec
calculate one or more eigenvectors in a DT volume.
tend evecrgb
make an RGB volume from an eigenvector and an anisotropy. π
tend evq
quantize directions of diffusion.
tend unmf
applies and removes the measurement frame.
tend expand
converts masked non-redundant tensor images to redundant.
tend shrink
converts a 9-value DT volume to a 7-value DT volume.
tend bfit
non-linear least-squares fitting of b-value curves.
tend satin
generate a pretty synthetic DT volume. pretty is literally in the job description. π
π SEE ALSO π
bestie the whole friend group is here, go say hi: gprobe(1), ilk(1), mrender(1), miter(1), nrrdSanity(1), overrgb(1), puller(1), unu(1), vprobe(1), tend-about(1), tend-anhist(1), tend-anplot(1), tend-anscale(1), tend-anvol(1), tend-avg(1), tend-bfit(1), tend-bmat(1), tend-ellipse(1), tend-epireg(1), tend-estim(1), tend-eval(1), tend-evaladd(1), tend-evalclamp(1), tend-evalmult(1), tend-evalpow(1), tend-evec(1), tend-evecrgb(1), tend-evq(1), tend-exp(1), tend-expand(1), tend-fiber(1), tend-glyph(1), tend-grads(1), tend-helix(1), tend-log(1), tend-make(1), tend-mconv(1), tend-mfit(1), tend-msim(1), tend-norm(1), tend-point(1), tend-satin(1), tend-shrink(1), tend-sim(1), tend-slice(1), tend-sten(1), tend-tconv(1), tend-triple(1), tend-unmf(1). π
and that's the whole page bestie!! this one wasTEND(1)β aUser Commandsmoment β and it dropped way back in April 2021. periodt. π β¨π¦
π¦ where this page comes from
- fedora 43: teem 1.11.0-83.fc43 Β· LGPL-2.1-or-later WITH LicenseRef-Fedora-Temporary-Simple-Library-exception
- fedora 43: teem 1.11.0-86.fc43 Β· LGPL-2.1-or-later WITH Simple-Library-Usage-exception
- fedora 44: teem 1.11.0-87.fc44 Β· LGPL-2.1-or-later WITH Simple-Library-Usage-exception
- π girlified by deepseek-ai/DeepSeek-V4.1-Flash on : a language model's rewrite of the original, under its terms