MICCAI 2019
Experience
MICCAI 2019 was a great experience. It was my first time in China, I experienced huge cultural difference and also huge difficult in ordering food. (once it took me 30 min to ask “if they have any vegitarian food”, finally ended with only soup 😔). Conference was organized at Intercontinental, they really had an amazing ambiance. Conference started from 13th Octobar, huge crowd working on amazing problems and contributing to medical imaging and medical image analysis research.
Few imp. things at MICCAI
Hypergraphs and their applications in biomedical image analysis
+ This was the first event which I attended, it was kind of new topic to me, as I've previously worked on graphs and graph networks, I could relate and understand the topics discussed in workshop
+ The workshop organizers also discussed few interesting applications of hypergraphs in medical domain, like classification using multi modal data and image registration along with low rank data representation
Domain adaptation and GAN
+ This workshop was joint organized by Kamnistas, Jailmer and Anirban, Everyone discussed few of their amazing work on domain adaptation and GAN
+ Domain Adaptation: Active line of research which tries to address model generalization on completely unseen dataset. In case of biomedical data, we train the model on one specific site but when deployment it needs to be generalized to multiple sites
+ Domain Adaptation concepts are more closer towards transfer learning, confounding seperation and optimal transport problems
+ GAN: Interesting research work was presented by Jailmer, which includes (1) MRI2CT, (2) Low res, High res conversion, (3) Progressive approach of training GANs
+ I also got a chance to discuss with Jailmer, on how we could merge graphs with GANS
Industrial lectures
+ Nice to haveVs Must have
+ Medium term to long term analysis
+ Data quality
+ Having add-ons
+ Convince patients not just doctors
Computational Pathology
+ Stain normalization
+ Neuclick talk
Posters
+ Federated learning
+ Universal representation Learning
+ Self inversion networks
Networking
Posters
Fire Dragon Show
Shenzhen sightseeing
My Presentation
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