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Swedish Bioinformatics Workshop 2021

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Fabian is the director of the Institute of Computational Biology at the Helmholtz Center Munich and scientific director of the Helmholtz Artificial Intelligence Cooperation Unit (HelmholtzAI) which was launched in 2019. He is a full professor at the Technical University of Munich, holding the chair'Mathematical Modelling of Biological Systems', associate faculty at the Wellcome Trust Sanger Institute as well as adjunct faculty at the Northwestern University. Fabian holds a Master's degree in Mathematics and Physics and Ph.D. Degrees in Physics and Computer Science. He worked as visiting researcher at the Department of Architecture and Computer Technology (University of Granada, Spain), at the RIKEN Brain Science Institute (Wako, Japan), at FAMU-FSU (Florida State University, USA), and TUAT's Laboratory for Signal and Image Processing (Tokyo, Japan), and headed the'signal processing & information theory' group at the Institute of Biophysics (Regensburg, Germany). In 2006, he started working as a Bernstein fellow leading a junior research group at the Bernstein Center for Computational Neuroscience, located at the Max Planck Institute for Dynamics and Self-Organisation at Göttingen.


Microscopes Improved With Artificial Intelligence

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To observe the swift neuronal signals in a fish brain, scientists have started to use a technique called light-field microscopy, which makes it possible to image such fast biological processes in 3D. But the images are often lacking in quality, and it takes hours or days for massive amounts of data to be converted into 3D volumes and movies. Now, EMBL scientists have combined artificial intelligence (AI) algorithms with two cutting-edge microscopy techniques - an advance that shortens the time for image processing from days to mere seconds, while ensuring that the resulting images are crisp and accurate. The findings are published in Nature Methods. "Ultimately, we were able to take'the best of both worlds' in this approach," says Nils Wagner, one of the paper's two lead authors and now a PhD student at the Technical University of Munich.


Artificial intelligence makes great microscopes better than ever

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To observe the swift neuronal signals in a fish brain, scientists have started to use a technique called light-field microscopy, which makes it possible to image such fast biological processes in 3D. But the images are often lacking in quality, and it takes hours or days for massive amounts of data to be converted into 3D volumes and movies. Now, EMBL scientists have combined artificial intelligence (AI) algorithms with two cutting-edge microscopy techniques--an advance that shortens the time for image processing from days to mere seconds, while ensuring that the resulting images are crisp and accurate. The findings are published in Nature Methods. "Ultimately, we were able to take'the best of both worlds' in this approach," says Nils Wagner, one of the paper's two lead authors and now a Ph.D. student at the Technical University of Munich.


Artificial intelligence makes great microscopes better than ever

#artificialintelligence

To observe the swift neuronal signals in a fish brain, scientists have started to use a technique called light-field microscopy, which makes it possible to image such fast biological processes in 3D. But the images are often lacking in quality, and it takes hours or days for massive amounts of data to be converted into 3D volumes and movies. Now, EMBL scientists have combined artificial intelligence (AI) algorithms with two cutting-edge microscopy techniques - an advance that shortens the time for image processing from days to mere seconds, while ensuring that the resulting images are crisp and accurate. The findings are published in Nature Methods. "Ultimately, we were able to take'the best of both worlds' in this approach," says Nils Wagner, one of the paper's two lead authors and now a PhD student at the Technical University of Munich.


Scientists Use AI To Create Transparent 3D Images of Organs

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Assembling an accurate image of what the inside of an organ looks like is not an easy task. In order to figure out what the inside of a liver or eyeball or brain looks like, said organs often need to be sliced into tiny slivers, which are then individually studied with a microscope. But now, another method of studying the insides of organs--which utilizes AI and a process called "tissue clearing"--is allowing researchers to study these biological structures in a way that's not only far less work-intensive, but also more conducive to understanding how they actually work. Futurism reported on the new process, which has been dubbed "Small-micelle-mediated Human orgAN Efficient clearing and Labeling" or SHANEL. The process is being developed by researchers in Germany, from Helmholtz Zentrum München (a research center), the LMU University Hospital Munich, and the Technical University of Munich.


Boston Dynamics Lets the Dogs Out; Google Releases Deepfake Detection Dataset

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Boston Dynamics' Robot Dog Is Now Available for Select Customers Boston Dynamics has begun commercialization of its robodog Spot. The company released a video on Tuesday that shows Spot navigating challenging terrain, picking up construction objects, moving through bad weather, and picking itself up after a fall. Boston Dynamics' Atlas Can Now Do An Impressive Gymnastics Routine Alongside the news that Boston Dynamics is letting robot dog Spot out of its laboratory for the first time, the company has released a new video of Atlas, a spectacular bipedal robot that's previously been seen doing everything from parkour to backflips. Contributing Data to Deepfake Detection Research In collaboration with Jigsaw, Google has announced the release of a large dataset of visual deepfakes they have produced. The data has been incorporated into the Technical University of Munich and the University Federico II of Naples' new FaceForensics benchmark, an effort that Google co-sponsors.


ImFusion Is Taking Medical Imaging to Another Dimension NVIDIA Blog

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Medical imaging provides a window into the human body, allowing us to see under the skin. But to really understand what's going on inside our bodies, doctors need 3D imagery. And there's no time this would be more helpful than during surgery. Now, ImFusion, a Munich-based startup and NVIDIA Inception program member, is taking medical imaging into the next dimension. It's using AI to turn 2D ultrasound data into 3D images.