Life Beyond the Pixels: Deep Learning Methods for Single Cell Analysis

Webinar On-Demand


Our guest speaker Prof. Dr. Peter Horvath presents his work on single cell-based large-scale microscopy experiments. This novel targeting approach includes the use of machine learning models and ultimately enables successful DNA and RNA sequencing, proteomics, lipidomics and targeted electrophysiology measurement on selected cells.

Speaker: Prof. Dr. Peter Horvath

Prof. Dr. Peter Horvath is currently the director and a group leader at the Biological Research Center in Szeged and holds a Finland Distinguished Professor (FiDiPro) Fellow position at the Institute for Molecular Medicine Finland, Helsinki. He graduated as a software engineer and received his Ph.D. from INRIA and University of Nice, Sophia Antipois, France in satellite image analysis. He is the co-founder of the European Cell-based Assays Interest Group and the councilor of the Society of Biomolecular Imaging and Informatics.

This webinar showcases

  • A novel microscopic image correction method designed to eliminate illumination and uneven background effects
  • New single-cell image segmentation methods using differential geometry, energy minimization and deep learning methods
  • The Advanced Cell Classifier (ACC), a machine learning software tool capable of identifying cellular phenotypes based on features extracted from the image

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