Biomedical Image Processing with Containers and Deep Learning

Data architecture, artificial intelligence, automated processing, containerization, and clusters orchestration ease the transition from data acquisition to insights in medium‐to‐large datasets. In this journal paper, Sierra’s researchers, in collaboration with PNP Research Corporation (MA, USA) and the Wellman Center for Photomedicine (Boston, MA, USA), discuss how to handle large microscopy datasets and process them automatically…

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Deep Learning for Biomarker Regression. Application to Osteoporosis and Emphysema on Chest CT Scans

Biomarker computation using deep-learning often relies on a two-step process, where the deep learning algorithm segments the region of interest and then the biomarker is measured. We propose an alternative paradigm, where the biomarker is estimated directly using a regression network. We showcase this image-to- biomarker paradigm using two biomarkers: the estimation of bone mineral…

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Disease Staging and Prognosis in Smokers Using Deep Learning in Chest Computed Tomography

What can Artificial Intelligence infer from computed tomography images of smokers? In this Journal publication, Sierra’s researchers in union with Brigham and Women’s Hospital and Partners develop staging and prognosis models for subjects suffering from COPD. The neural networks are thoroughly tested in several large databases, obtaining high areas under the curve. The full article…

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