Dr. Žagar and Dr. Mutka win second place at EIT Jumpstarter Grand Finals!



November 30, 2020

Our Web and Mobile Computing faculty Dr. Martin Žagar and Dr. Alan Mutka won second place at EIT Jumpstarter’s Grand Finals with their idea "Efficient Motion Detection Algorithm for 3D Medical Data” (MMD3D) in the area of EIT Health. They contended with 120 teams selected for this competition. The grand finals took place in an online environment on November 25th, 2020.

EIT Jumpstarter is one of the widest cross-industrial programs designed for early-stage innovators in six knowledge and innovation communities: EIT Raw Materials, EIT Health, EIT Food, EIT InnoEnergy, EIT Manufacturing, and EIT Urban Mobility, initiated and funded by the EIT. Their main idea is to help innovators bring their ideas to life. After analyzing a number of submitted proposals, 120 teams are selected to compete out of which 90 are selected to validate their business plan. Next, the top 36 teams are selected for the Joint Grand Final and then 3 in each category are selected as prize winners.


 

The MMD3D team was winner of the second prize of the "EIT Jumpstarter – Health Category", a joint program by EIT Health, EIT RawMaterials EIT Food, EIT Innoenergy, EIT Urban Mobility and EIT Manufacturing. KICs are supported by the EIT, a body of the European Union.


"We proposed our idea in the domain of EIT Health”, says Dr. Žagar. "At first, we applied to find a proof for our idea, but ended up producing a complete business plan together with the value proposition! Namely, our idea is based on the premise that the encoding and streaming of medical video for diagnosis purposes is an example of computationally demanding applications. Motion detection presents one of the pillars in encoding such videos and a basis for compression where just motion vectors are encoded instead of the complete data frame. We proposed a new algorithm for motion detection of 3D medical videos where the novel approach is based on the fact that medical videos don’t have sudden and large motions and that the motion is coherent through the data frames.”

"Having our idea selected among the best ones made us proud because we proved our initial hypothesis!", continues Dr. Žagar. „Now we have reached TRL 3 (Technology Readiness Level) which means we successfully accomplished the proof-of-concept stage. The next step would be to find a business partner for deployment and market approach later. We continue to research and think about the innovative ideas that will produce new applications for some other competitions and research projects."

 

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