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A new approach to machine learning image analysis learns much more quickly and requires far fewer images

By reducing the amount of required training images and increasing the size of images that can be processed, the new architecture can be used to answer important questions in many research fields. ....

University Of California San Francisco , United States , Noord Brabant , James Sethian , Wiskunde Informatica , Olivia Jain , Simon Mo , Carolyn Larabell , National Center , Computational Research Division , Mathematics For Energy Research Applications , Office Of Science , Department Of Energy , Scale Dense Convolution Neural Networks , University Of California , Scale Dense Convolution Neural Network , Berkeley Lab , Computational Imaging Group , Lawrence Berkeley National Laboratory , Proceedings Of The National Academy Sciences , Advanced Mathematics , Energy Research Applications , Computational Research , National Academy , Centrum Wiskunde , Labeled Image Data Engine ,

Scientists now able to predict response to radium-223 treatment in prostate cancer bone metastases

Scientists now able to predict response to radium-223 treatment in prostate cancer bone metastases
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City Of , United Kingdom , Matthew Blackledge , Chris Parker , Ricardo Donners , Institute Of Cancer Research , Computational Imaging Group , European Radiology , Cancer Research , Royal Marsden , Professor Chris Parker , Clinical Oncology , Prostate Cancer , Prostate Oncology , Professor Dow Mu Koh , Consultant Radiologist , Functional Imaging , Functional Cancer Imaging ,

Bio-FlatScope Captures Cellular-Level, 3D Details in Living Tissue

Bio-FlatScope captures images that no lensed camera can see showing, for example, dynamic changes in the fluorescent-tagged neurons in running mice. ....

Vivek Boominathan , Jimin Wu , Ashok Veeraraghavan , Jacob Robinson , Rice University Bio , Computational Imaging Group , Rice University , Nature Biomedical Engineering ,

Artificial Intelligence Spots Anomalies in Medical Images

Artificial Intelligence Spots Anomalies in Medical Images
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Dmitry Dylov , Irina Fedulova , Philips Research , Goethe University Frankfurt , Institute Computational Imaging Group , Skoltech Professor Dmitry Dylov , Computational Imaging Group , Deep Perceptual Autoencoders ,

Training Neural Network to Detect Anomalies in Medical Images

Researchers from Skoltech, Philips Research, and Goethe University Frankfurt have trained a neural network to identify anomalies in medical images to help physicians in screen through countless scans in search of pathologies. ....

Dmitry Dylov , Irina Fedulova , Head Of The Institute Computational Imaging Group , Philips Research , Study Co , Philips Research Branch , Lomonosov Moscow State University , Goethe University Frankfurt , Skolkovo Institute Of Science , Study Senior Author , Computational Imaging Group , Skolkovo Institute , Deep Perceptual Autoencoders , Study Co Author , Lomonosov Moscow State ,