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Author Archives: mauricio reyes
2020…
To many of us 2020 is a year to forget. The pandemic brought not only confinement, uncertainty and darkness to our lives, but also a greater awareness about the fragility of our world. As a researcher working in medtech, I … Continue reading
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Still around! news and others
I haven’t posted much on my website due to technical issues with my WordPress social network plugins :S , which led me to post mostly (directly) in Twitter and LinkedIn.. I am very happy to announce that our review paper … Continue reading
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new MICCAI 2018 workshop announcement
Glad to announce iMIMIC, a new workshop on Interpretability of Machine Intelligence in Medical Image Computing at Miccai 2018. Check out our website at https://imimic.bitbucket.io where we will be posting more information Check out as well our promotional video here: Enjoy! … Continue reading
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Clinical Neuroscience Bern – Science Slam is back this year!
The Clinical Neuroscience Bern network organises every year the Science Slam event, a great initiative to bring neuroscientists to one place; share ideas and challenges in an entertaining and informative manner. If you haven’t yet, check out our 2017 contribution … Continue reading
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Best seven books to check out in 2018 for Machine/Deep Learning and Medical Image Computing
Whether you are teacher, student, computer scientist, or proficient machine learning programmer, there are many times where having a solid reference library on the topic can save you a lot of time and help you to prepare material for your next … Continue reading
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New findings on enhancing interpretability of automatically extracted machine learning features
Sharing recent findings on Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation https://authors.elsevier.com/c/1WKpf4rfPluH2D Abstract: Machine learning systems are achieving better performances at the cost of becoming increasingly complex. However, because of that, … Continue reading
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New findings in automated GBM volumetry, extent of resection and residual tumor
Discover our new findings on automated volumetry for extent-of-resection and residual-tumor for GBM patients. Journal of NeuroSurgery Meier et al. 2016. http://thejns.org/doi/full/10.3171/2016.9.JNS16146
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Porz et al. PlosOne2016 – Fully Automated Enhanced Tumor Compartmentalization: Man vs. Machine Reloaded
New findings in #BrainTumors volumetry. BraTumIA @unibern @inselgruppe and @BrainLab SmartBrush. Multiple experts http://dx.doi.org/10.1371/journal.pone.0165302
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Introducing FASTER – Fully automated stroke tissue estimation using random forest classifiers
New developments in stroke tissue estimation. Introducing FASTER – Fully Automated Stroke Tissue Estimation using Random forest classifiers. McKinley et al. JCBFM 2016 http://dx.doi.org/10.1177/0271678X16674221
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Miccai award
Highly grateful for recognition @miccai2016 Collaborative effort @unibern @inselgruppe Stefan Bauer Young Scientist Publication Impact Award
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