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AI and Deep learning in Biomedical Image analysis

Time: Thu 2018-11-22 09.15 - 10.00

Location: FB42

Participating: Anindya Gupta,Post-doctoral researcher, Department of Information Technology, Uppsala University

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Computerized image analysis workflows have facilitated the clinicians/researchers with improved characterization of biological structures for comprehending obscure abnormalities. Previously, the workflows employing classical image analysis methods were explicitly designed for problem-specific solutions. Since the inception of deep learning as a powerful recognition method, the research interest has shifted from problem-specific solutions to increasingly problem-agnostic solutions that rely on learning from data. In particular, convolutional neural networks (CNNs) have rapidly become a primary choice due to its promising results. Given the prevalence of deep learning methods, I will briefly discuss the underlying concepts of CNN and also highlight their applications in multiple tasks of an automated workflow, e.g., pre-processing, segmentation, classification, etc.

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Last changed: Nov 15, 2018