KardioMe

For a world without heart diseases.

Cardiac image analysis | 3D printing

[Jan Margeta @jmargeta]

Our book on Advancing Cochlear Implants is out!
See the magic behind a tech that makes people hear and be heard.

Kudos to the amazing co-authors and editors of our chapter on imaging & AI @PaulaLopezDiez, Behnam Molaee-Ardekani, Thomas Demarcy, Manuel Segovia-Martinez.

Link👇

[Paula López Diez @PaulaLopezDiez]

🔍New Publication!📚Comparing our deep reinforcement learning approach with convolutional autoencoders for detecting inner ear malformations on CT, we've enhanced detection accuracy by 11.2%! Read more: https://t.co/6jFqvYvgUs #MedicalImaging #DeepLearning #AnomalyDetection 🧠👂

[Jan Margeta @jmargeta]

First ever automatic classification of congenital inner ear malformations today at #MICCAI23 by @paulalopezdiez🌟

Find Paula today @ poster T04-112 and learn how we represent diverse cochlear shapes from normal, hypoplasia, incomplete partition I-III, common cavity to aplasia👇

[Jan Margeta @jmargeta]

Nautilus strikes again! We set our automated imaging platform to measure 1099 cochleae and our findings are now in JCM: https://t.co/zBfRq4A7zz

Well done, friends at @OticonMedical, @CHUdeNice, @InriaEpione, and @KardioMe!👏

#ent #otology #NewPaper #MedTwitter #Statistics #DL

[Jan Margeta @jmargeta]

The MLMI proceedings are out! Thanks to all for sharing your research. Special shoutout to the amazing duo Ana-Teodora Radutoiu and @PaulaLopezDiez for leading our paper on deep RL for inner ear localization
https://t.co/wHYJRfsWrO
#deeplearning #cochlea #miccai #teosdebut #hny🎉

[Jan Margeta @jmargeta]

We've built a comprehensive cochlear image analysis tool to enable large scale studies, enabling access to cutting-edge #ML from the browser

How? We detail the pipeline in our paper that has just been published in the Journal of Clinical Medicine:
https://t.co/srdpuPdBTB

[Jan Margeta @jmargeta]

⚡️Time to reinforce some 🐌 nerves #MICCAI2021⚡️
Our Paula López Diez presents: "Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection"
With @JosefineLl @FrancoisPatou Rasmus R Paulsen @OticonMedical @DTU_Compute @kardiome

[Jan Margeta @jmargeta]

Let's all contain the #COVID19 spread within manageable bounds and healthcare systems' capacities

Proud of our talented #hackthecrisis team🚀
💡 real-time local symptom analytics for crisis mgmt and researchers
📺 https://t.co/3JJKfbos9P
🥈 is a bonus
Early @kardiome memories🙋

[KardioMe @kardiome]

Check out slidedecks from two of our latest talks for a bit of #MachineLearning in #CardiacImaging, #3DPrinted personalized #Cardiac models, a sprinkle of #VirtualReality, or #ComputerVision in general, and quite a bit of #python https://t.co/odaMnmDNmN

[Jan Margeta @jmargeta]

Hey #PyDays18, what a fantastic day yesterday! Even more excited for today's #Python goodness. Thanks for all the nice interactions! Slides: https://t.co/7Nnw4dOCxB. More on vision or differentiable programming https://t.co/3YBmV3BXjA #mxnet #gluon #opencv @ApacheMXNet @pyconsk

[Jan Margeta @jmargeta]

Was fantastic to discuss Python, ML, medical imaging, and @kardiome today. Thank you all for joining and your wonderful questions! #PyConSK

[KardioMe @kardiome]

How to 3d print functional heart muscle
1-use heart cells + collagen as filament
2-print
3-melt away the collagen
4-train the cells in a gym https://t.co/m8YQYNwwvM

[90.5 WESA @905wesa]

No plastic here. This @CMUEngineering professor uses cells and collagen to 3-D print heart tissue https://t.co/ZlRNZLxfJm

[KardioMe @kardiome]

Could we reduce the need for MRI contrast agents by tagging the blood? Yes! Welcome myocardial ASL: https://t.co/QpvgjBgmbN

[KardioMe @kardiome]

A great step towards 3d printing of soft-tissue embryonic (chick) hearts! https://t.co/PHT3X3ok7l