We are the Robotics and Vision in Medicine Lab. We design and develop image-guided microsurgical robots for regenerative therapy delivery @KingsImaging.
London, England
Joined July 2017
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Robotics and Vision in Medicine Lab retweeted
Success for Black Engineers is a King’s College London Engineering programme designed to support aspiring Black engineers at school and university.
Hear from PhD student Shaheim Ogbomo-Harmitt about his experience.
Find out more about the programme: kcl.ac.uk/bmeis/blackenginee…
Robotics and Vision in Medicine Lab retweeted
Panel discussion of our @ieee_ras_icra workshop on "#Growing #Robots" by @BarbaraMazzolai, Allison Okamura, @katzschmann, Laura Blumenschin, hosted by @taniamorimoto
Stay tuned for the @MathWorks' poster prizes 🎊
@KingsImaging @rvimlab
Robotics and Vision in Medicine Lab retweeted
Thank you for the invitation to present MAMMOBOT! The project would not have started if not for the sandpit of @CRUKresearch and @EPSRC on robotic tech for early cancer detection in 2019. Looking forward to building on our results and moving the project forward.
📢The first keynote speaker is @bergeles of @rvimlab in @KingsImaging presenting the 'MAMMOBOT' project, a flexible robot for early #BreastCancer detection and intervention highlighting the clinical and societal need, as 55,000 women are diagnosed with #BreastCancer per year (AB)
Robotics and Vision in Medicine Lab retweeted
#ICRA2023 will host 12 robotics competitions in areas including humanoid robots, mobile robots, legged robots, robot manipulation and grasping, aerial vehicles, and important topics such as ethics. Some are still open for registration! Check details here icra2023.org/competitions
Robotics and Vision in Medicine Lab retweeted
Join our Summer Workshop on Surgical & Interventional Engineering 👩💻
Ideal for those working on industrial, academic or clinical R&D environments:
-roboticists
-optics engineers
-computer scientists
-clinical research fellows
Find out more: kcl.ac.uk/short-courses/surg…
Robotics and Vision in Medicine Lab retweeted
Want to do a industry-funded PhD on active learning and human-AI interaction, aiming to improve medical imaging data labelling? Apply below (international applicants, deadline 1st March)
Joint with @SiemensHealth & building on @ProjectMONAI Label
kcl.ac.uk/study-legacy/fundi…
Robotics and Vision in Medicine Lab retweeted
Apply now for our fully funded PhD studentships with #SurgeryCDT for a 1st Feb 2023 start.
Further details: surgerycdt.com/how-to-apply
Applications close: 20th Nov 2022
#phd #phdopportunity #phdposition
Robotics and Vision in Medicine Lab retweeted
Join our Toronto AIR Seminar on 10/24 at 10:30 am E.T. to hear @SMHadiSadati’s recent work, Reinventing Catheters by Soft Robotics: Robotics Thrombectomy for Acute Stroke!!
More info: robotics.cs.toronto.edu/toro…
Zoom: utoronto.zoom.us/j/821194786…
Robotics and Vision in Medicine Lab retweeted
And that's a wrap!
With over 100 volunteers over 3 days and 15 interactive demonstrations, our Hospital of the Future was an overwhelming success for all visitors to New Scientist Live 2022 -- the first live show since 2019! kcl.ac.uk/news/heartwarming-… #healthcare #technology
Congratulation to Theodoros Pissas (@pis_tho) who passed his PhD examination at @UCLmedphys. Theo was a PhD student and Research Assistant @KingsImaging with the team since 2017, and carried out research on #computer #vision #semantic #segmentation.
Theo's most recent acheivement is his @eccvconf 2022 paper on multi-scale and cross-scale #contrastic #learning for pixel-level semantic segmentation. The paper can be found here:
lnkd.in/eGNGmeWG
while the source code is given here:
lnkd.in/eVDYpPds
Robotics and Vision in Medicine Lab retweeted
⏰ it's almost time! ⏰
Just one week left to apply for a PhD at our
Surgical & Interventional Engineering CDT! Browse our #PhD projects & submit your application to join #surgerycdt in October.
Details 👉 surgerycdt.com/how-to-apply
Well done @pis_tho on your #ECCV2022 paper. Your approach is easy to introduce to a variety of common architectures, and clearly shows improvements over the state-of-the-art results on challenging datasets.
Happy to share our paper on multi-scale and cross-scale contrastive learning for semantic segmentation was accepted at #ECCV2022. Our paper is on arxiv arxiv.org/abs/2203.13409. Short thread on the main ideas in the paper:
Medical datasets are a treasure trove of information. How does one separate useful information from noise, however? Manual curation of datasets is a monumental task, yet curation is a prerequisite to making sense of relationships within data.
R esearch was funded by Diabetes UK, and carried out in collaboration with @pnderitu89, Joan M. Nunez do Rio, Laura Webster, Samantha Mann, David Hopkins, @mjorgecardoso, @mmodat and Tim Jackson.