@hekr #TotalSegmenter was super easy to use for a #CT cervical spine dataset. Thank you for point me to this...

#MedicalImaging

#MedicalImaging #Visualization Software

I am working on a list of software for the visualization, processing, and analysis of medical images. Currently includes:

3D Slicer: https://slicer.org
MITK: https://www.mitk.org
MIPAV: https://mipav.cit.nih.gov
ImageJ: https://imagej.net
FSLEyes: https://fsl.fmrib.ox.ac.uk

I like Slicer, generally, as it is comprehensive. MIPAV I use when I want to overlay two images and do an interactive comparison.

Other good ones?

#MRI #CT

📅 Don't forget papers for the #FAIMI fairness in medical imaging #MICCAI2023 workshop are due

*July 21 2023*

Accepted papers will be published in Springer LNCS proceedings, see our website for more details

https://faimi-workshop.github.io/2023-miccai/

#MachineLearning #MedicalImaging #Fairness

Recently started using #obsidian (https://obsidian.md). It is a Markdown Wiki style editor, similar to Notion, where you can write, link, paste images etc and has auto-commit to Git. But everything is local.

It has been an amazing resource for doing #medicalimaging ad #ai research, tracking projects and task management. The tasks are one of the big reasons I came to it.

(The money-bag on Grants should probably have a red circle with line through it. :) )

Curious if others use it...

📝 Read our call for papers here: https://faimi-workshop.github.io/2023-miccai/

#MedicalImaging #MachineLearning #AI #FairAI

If you have any questions please reach out to us via faimi-organizers@googlegroups.com!

3/3

🚨 Are you interested in the Fairness of Artificial Intelligence for Medical Imaging? Don't miss our next #FAIMI workshop at #MICCAI2023!

⏰Papers due: Jul 21, 2023
📅Workshop: Oct 8, 2023
📍Where: Vancouver 🇨🇦

Check out: https://faimi-workshop.github.io/2023-miccai/

#MedicalImaging #Fairness #MachineLearning 1/3

Many people working on #MachineLearning algorithms assume the data is already there, but there's a lot of work behind the scenes! If you want to learn about how some #MedicalImaging challenge datasets were made, join our next "Datasets through the L👀king-Glass" webinar, organized by @amelia

🗓️ Date: 5th June 2023
🕓 4pm CEST
💻 Where: Zoom. Register at https://shorturl.at/horRW

🔗 https://purrlab.github.io/webinar/

#MakingMetadataCount

The postdoc position #MachineLearning #MedicalImaging #HCI I'm hiring for is finally online! Please reach out if you might be interested, if you happen to be at #CHI2023 physically or virtually we can talk offline or on the Discord channel! https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181571&DepartmentId=3439&MediaId=338

Question to the #AI / #aiethics community:

Can anyone recommend me some #guidelines or #checklist of best practices in #ML?

I am quite used to the PRIME checklist (but it is more focused on #MedicalImaging).

I have found many but few incorporate uncertainty, fairness, ethical considerations....

Thanks :)

Totalsegementator - not only iis the tool open source but also available for 3Dslicer as an extension. Example segmentation of thorax on coarse setting (without GPU and an old Athlon CPU), takes < 5 min.
Github: https://github.com/wasserth/TotalSegmentator
3D Slicer: https://discourse.slicer.org/t/new-extension-fully-automatic-whole-body-ct-segmentation-in-2-minutes-using-totalsegmentator/26710
#DeepLearning #TotalSegmentator #OpenSource #RadOnc #MedicalImaging #3DSlicer #Contouring

#introduction
Hello! I am a medical doctor turned scientist (Dr^2).

I use MRI in conjunction with other data to measure disease progression and response to treatment in #chronicpain, #stroke, #SVD, and #dementia.

Pet project: outcomes and control groups in #clinicaltrials to account for #placebo / #nocebo

I also run (mostly off-road), take #photos (sometimes while running), drink coffee (mostly asleep), and wine (mostly blinded).

Hashtag collection:
#MedicalImaging
#WomenInSTEM